Instructions to use fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF with sentence-transformers:

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF")

sentences = [
    "That is a happy person",
    "That is a happy dog",
    "That is a very happy person",
    "Today is a sunny day"
]
embeddings = model.encode(sentences)

similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4]

Transformers

How to use fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF:Q8_0

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF:Q8_0

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF:Q8_0

Use Docker

docker model run hf.co/fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF:Q8_0

LM Studio
Jan
Ollama
How to use fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF with Ollama:
```
ollama run hf.co/fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF:Q8_0
```

Unsloth Studio

How to use fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF to start chatting

Docker Model Runner
How to use fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF with Docker Model Runner:
```
docker model run hf.co/fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF:Q8_0
```

Lemonade

How to use fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF:Q8_0

Run and chat with the model

lemonade run user.gte-Qwen2-7B-instruct-Q8_0-GGUF-Q8_0

List all available models

lemonade list

Atomic Chat

fishbone64 commited on Jun 26, 2024

Commit

486b6d5

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1 Parent(s): 30f8b74

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+---
+base_model: Alibaba-NLP/gte-Qwen2-7B-instruct
+license: apache-2.0
+tags:
+- mteb
+- sentence-transformers
+- transformers
+- Qwen2
+- sentence-similarity
+- llama-cpp
+- gguf-my-repo
+model-index:
+- name: gte-qwen2-7B-instruct
+  results:
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonCounterfactualClassification (en)
+      type: mteb/amazon_counterfactual
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 91.31343283582089
+    - type: ap
+      value: 67.64251402604096
+    - type: f1
+      value: 87.53372530755692
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonPolarityClassification
+      type: mteb/amazon_polarity
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 97.497825
+    - type: ap
+      value: 96.30329547047529
+    - type: f1
+      value: 97.49769793778039
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonReviewsClassification (en)
+      type: mteb/amazon_reviews_multi
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 62.564
+    - type: f1
+      value: 60.975777935041066
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB ArguAna
+      type: mteb/arguana
+      config: default
+      split: test
+      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
+    metrics:
+    - type: map_at_1
+      value: 36.486000000000004
+    - type: map_at_10
+      value: 54.842
+    - type: map_at_100
+      value: 55.206999999999994
+    - type: map_at_1000
+      value: 55.206999999999994
+    - type: map_at_3
+      value: 49.893
+    - type: map_at_5
+      value: 53.105000000000004
+    - type: mrr_at_1
+      value: 37.34
+    - type: mrr_at_10
+      value: 55.143
+    - type: mrr_at_100
+      value: 55.509
+    - type: mrr_at_1000
+      value: 55.509
+    - type: mrr_at_3
+      value: 50.212999999999994
+    - type: mrr_at_5
+      value: 53.432
+    - type: ndcg_at_1
+      value: 36.486000000000004
+    - type: ndcg_at_10
+      value: 64.273
+    - type: ndcg_at_100
+      value: 65.66199999999999
+    - type: ndcg_at_1000
+      value: 65.66199999999999
+    - type: ndcg_at_3
+      value: 54.352999999999994
+    - type: ndcg_at_5
+      value: 60.131
+    - type: precision_at_1
+      value: 36.486000000000004
+    - type: precision_at_10
+      value: 9.395000000000001
+    - type: precision_at_100
+      value: 0.996
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 22.428
+    - type: precision_at_5
+      value: 16.259
+    - type: recall_at_1
+      value: 36.486000000000004
+    - type: recall_at_10
+      value: 93.95400000000001
+    - type: recall_at_100
+      value: 99.644
+    - type: recall_at_1000
+      value: 99.644
+    - type: recall_at_3
+      value: 67.283
+    - type: recall_at_5
+      value: 81.294
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB ArxivClusteringP2P
+      type: mteb/arxiv-clustering-p2p
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 56.461169803700564
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB ArxivClusteringS2S
+      type: mteb/arxiv-clustering-s2s
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 51.73600434466286
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB AskUbuntuDupQuestions
+      type: mteb/askubuntudupquestions-reranking
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 67.57827065898053
+    - type: mrr
+      value: 79.08136569493911
+  - task:
+      type: STS
+    dataset:
+      name: MTEB BIOSSES
+      type: mteb/biosses-sts
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.53324575999243
+    - type: cos_sim_spearman
+      value: 81.37173362822374
+    - type: euclidean_pearson
+      value: 82.19243335103444
+    - type: euclidean_spearman
+      value: 81.33679307304334
+    - type: manhattan_pearson
+      value: 82.38752665975699
+    - type: manhattan_spearman
+      value: 81.31510583189689
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB Banking77Classification
+      type: mteb/banking77
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 87.56818181818181
+    - type: f1
+      value: 87.25826722019875
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB BiorxivClusteringP2P
+      type: mteb/biorxiv-clustering-p2p
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 50.09239610327673
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB BiorxivClusteringS2S
+      type: mteb/biorxiv-clustering-s2s
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 46.64733054606282
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackAndroidRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: f46a197baaae43b4f621051089b82a364682dfeb
+    metrics:
+    - type: map_at_1
+      value: 33.997
+    - type: map_at_10
+      value: 48.176
+    - type: map_at_100
+      value: 49.82
+    - type: map_at_1000
+      value: 49.924
+    - type: map_at_3
+      value: 43.626
+    - type: map_at_5
+      value: 46.275
+    - type: mrr_at_1
+      value: 42.059999999999995
+    - type: mrr_at_10
+      value: 53.726
+    - type: mrr_at_100
+      value: 54.398
+    - type: mrr_at_1000
+      value: 54.416
+    - type: mrr_at_3
+      value: 50.714999999999996
+    - type: mrr_at_5
+      value: 52.639
+    - type: ndcg_at_1
+      value: 42.059999999999995
+    - type: ndcg_at_10
+      value: 55.574999999999996
+    - type: ndcg_at_100
+      value: 60.744
+    - type: ndcg_at_1000
+      value: 61.85699999999999
+    - type: ndcg_at_3
+      value: 49.363
+    - type: ndcg_at_5
+      value: 52.44
+    - type: precision_at_1
+      value: 42.059999999999995
+    - type: precision_at_10
+      value: 11.101999999999999
+    - type: precision_at_100
+      value: 1.73
+    - type: precision_at_1000
+      value: 0.218
+    - type: precision_at_3
+      value: 24.464
+    - type: precision_at_5
+      value: 18.026
+    - type: recall_at_1
+      value: 33.997
+    - type: recall_at_10
+      value: 70.35900000000001
+    - type: recall_at_100
+      value: 91.642
+    - type: recall_at_1000
+      value: 97.977
+    - type: recall_at_3
+      value: 52.76
+    - type: recall_at_5
+      value: 61.148
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackEnglishRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
+    metrics:
+    - type: map_at_1
+      value: 35.884
+    - type: map_at_10
+      value: 48.14
+    - type: map_at_100
+      value: 49.5
+    - type: map_at_1000
+      value: 49.63
+    - type: map_at_3
+      value: 44.646
+    - type: map_at_5
+      value: 46.617999999999995
+    - type: mrr_at_1
+      value: 44.458999999999996
+    - type: mrr_at_10
+      value: 53.751000000000005
+    - type: mrr_at_100
+      value: 54.37800000000001
+    - type: mrr_at_1000
+      value: 54.415
+    - type: mrr_at_3
+      value: 51.815
+    - type: mrr_at_5
+      value: 52.882
+    - type: ndcg_at_1
+      value: 44.458999999999996
+    - type: ndcg_at_10
+      value: 54.157
+    - type: ndcg_at_100
+      value: 58.362
+    - type: ndcg_at_1000
+      value: 60.178
+    - type: ndcg_at_3
+      value: 49.661
+    - type: ndcg_at_5
+      value: 51.74999999999999
+    - type: precision_at_1
+      value: 44.458999999999996
+    - type: precision_at_10
+      value: 10.248
+    - type: precision_at_100
+      value: 1.5890000000000002
+    - type: precision_at_1000
+      value: 0.207
+    - type: precision_at_3
+      value: 23.928
+    - type: precision_at_5
+      value: 16.878999999999998
+    - type: recall_at_1
+      value: 35.884
+    - type: recall_at_10
+      value: 64.798
+    - type: recall_at_100
+      value: 82.345
+    - type: recall_at_1000
+      value: 93.267
+    - type: recall_at_3
+      value: 51.847
+    - type: recall_at_5
+      value: 57.601
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackGamingRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
+    metrics:
+    - type: map_at_1
+      value: 39.383
+    - type: map_at_10
+      value: 53.714
+    - type: map_at_100
+      value: 54.838
+    - type: map_at_1000
+      value: 54.87800000000001
+    - type: map_at_3
+      value: 50.114999999999995
+    - type: map_at_5
+      value: 52.153000000000006
+    - type: mrr_at_1
+      value: 45.016
+    - type: mrr_at_10
+      value: 56.732000000000006
+    - type: mrr_at_100
+      value: 57.411
+    - type: mrr_at_1000
+      value: 57.431
+    - type: mrr_at_3
+      value: 54.044000000000004
+    - type: mrr_at_5
+      value: 55.639
+    - type: ndcg_at_1
+      value: 45.016
+    - type: ndcg_at_10
+      value: 60.228
+    - type: ndcg_at_100
+      value: 64.277
+    - type: ndcg_at_1000
+      value: 65.07
+    - type: ndcg_at_3
+      value: 54.124
+    - type: ndcg_at_5
+      value: 57.147000000000006
+    - type: precision_at_1
+      value: 45.016
+    - type: precision_at_10
+      value: 9.937
+    - type: precision_at_100
+      value: 1.288
+    - type: precision_at_1000
+      value: 0.13899999999999998
+    - type: precision_at_3
+      value: 24.471999999999998
+    - type: precision_at_5
+      value: 16.991
+    - type: recall_at_1
+      value: 39.383
+    - type: recall_at_10
+      value: 76.175
+    - type: recall_at_100
+      value: 93.02
+    - type: recall_at_1000
+      value: 98.60900000000001
+    - type: recall_at_3
+      value: 60.265
+    - type: recall_at_5
+      value: 67.46600000000001
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackGisRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 5003b3064772da1887988e05400cf3806fe491f2
+    metrics:
+    - type: map_at_1
+      value: 27.426000000000002
+    - type: map_at_10
+      value: 37.397000000000006
+    - type: map_at_100
+      value: 38.61
+    - type: map_at_1000
+      value: 38.678000000000004
+    - type: map_at_3
+      value: 34.150999999999996
+    - type: map_at_5
+      value: 36.137
+    - type: mrr_at_1
+      value: 29.944
+    - type: mrr_at_10
+      value: 39.654
+    - type: mrr_at_100
+      value: 40.638000000000005
+    - type: mrr_at_1000
+      value: 40.691
+    - type: mrr_at_3
+      value: 36.817
+    - type: mrr_at_5
+      value: 38.524
+    - type: ndcg_at_1
+      value: 29.944
+    - type: ndcg_at_10
+      value: 43.094
+    - type: ndcg_at_100
+      value: 48.789
+    - type: ndcg_at_1000
+      value: 50.339999999999996
+    - type: ndcg_at_3
+      value: 36.984
+    - type: ndcg_at_5
+      value: 40.248
+    - type: precision_at_1
+      value: 29.944
+    - type: precision_at_10
+      value: 6.78
+    - type: precision_at_100
+      value: 1.024
+    - type: precision_at_1000
+      value: 0.11800000000000001
+    - type: precision_at_3
+      value: 15.895000000000001
+    - type: precision_at_5
+      value: 11.39
+    - type: recall_at_1
+      value: 27.426000000000002
+    - type: recall_at_10
+      value: 58.464000000000006
+    - type: recall_at_100
+      value: 84.193
+    - type: recall_at_1000
+      value: 95.52000000000001
+    - type: recall_at_3
+      value: 42.172
+    - type: recall_at_5
+      value: 50.101
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackMathematicaRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
+    metrics:
+    - type: map_at_1
+      value: 19.721
+    - type: map_at_10
+      value: 31.604
+    - type: map_at_100
+      value: 32.972
+    - type: map_at_1000
+      value: 33.077
+    - type: map_at_3
+      value: 27.218999999999998
+    - type: map_at_5
+      value: 29.53
+    - type: mrr_at_1
+      value: 25.0
+    - type: mrr_at_10
+      value: 35.843
+    - type: mrr_at_100
+      value: 36.785000000000004
+    - type: mrr_at_1000
+      value: 36.842000000000006
+    - type: mrr_at_3
+      value: 32.193
+    - type: mrr_at_5
+      value: 34.264
+    - type: ndcg_at_1
+      value: 25.0
+    - type: ndcg_at_10
+      value: 38.606
+    - type: ndcg_at_100
+      value: 44.272
+    - type: ndcg_at_1000
+      value: 46.527
+    - type: ndcg_at_3
+      value: 30.985000000000003
+    - type: ndcg_at_5
+      value: 34.43
+    - type: precision_at_1
+      value: 25.0
+    - type: precision_at_10
+      value: 7.811
+    - type: precision_at_100
+      value: 1.203
+    - type: precision_at_1000
+      value: 0.15
+    - type: precision_at_3
+      value: 15.423
+    - type: precision_at_5
+      value: 11.791
+    - type: recall_at_1
+      value: 19.721
+    - type: recall_at_10
+      value: 55.625
+    - type: recall_at_100
+      value: 79.34400000000001
+    - type: recall_at_1000
+      value: 95.208
+    - type: recall_at_3
+      value: 35.19
+    - type: recall_at_5
+      value: 43.626
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackPhysicsRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
+    metrics:
+    - type: map_at_1
+      value: 33.784
+    - type: map_at_10
+      value: 47.522
+    - type: map_at_100
+      value: 48.949999999999996
+    - type: map_at_1000
+      value: 49.038
+    - type: map_at_3
+      value: 43.284
+    - type: map_at_5
+      value: 45.629
+    - type: mrr_at_1
+      value: 41.482
+    - type: mrr_at_10
+      value: 52.830999999999996
+    - type: mrr_at_100
+      value: 53.559999999999995
+    - type: mrr_at_1000
+      value: 53.588
+    - type: mrr_at_3
+      value: 50.016000000000005
+    - type: mrr_at_5
+      value: 51.614000000000004
+    - type: ndcg_at_1
+      value: 41.482
+    - type: ndcg_at_10
+      value: 54.569
+    - type: ndcg_at_100
+      value: 59.675999999999995
+    - type: ndcg_at_1000
+      value: 60.989000000000004
+    - type: ndcg_at_3
+      value: 48.187000000000005
+    - type: ndcg_at_5
+      value: 51.183
+    - type: precision_at_1
+      value: 41.482
+    - type: precision_at_10
+      value: 10.221
+    - type: precision_at_100
+      value: 1.486
+    - type: precision_at_1000
+      value: 0.17500000000000002
+    - type: precision_at_3
+      value: 23.548
+    - type: precision_at_5
+      value: 16.805
+    - type: recall_at_1
+      value: 33.784
+    - type: recall_at_10
+      value: 69.798
+    - type: recall_at_100
+      value: 90.098
+    - type: recall_at_1000
+      value: 98.176
+    - type: recall_at_3
+      value: 52.127
+    - type: recall_at_5
+      value: 59.861
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackProgrammersRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
+    metrics:
+    - type: map_at_1
+      value: 28.038999999999998
+    - type: map_at_10
+      value: 41.904
+    - type: map_at_100
+      value: 43.36
+    - type: map_at_1000
+      value: 43.453
+    - type: map_at_3
+      value: 37.785999999999994
+    - type: map_at_5
+      value: 40.105000000000004
+    - type: mrr_at_1
+      value: 35.046
+    - type: mrr_at_10
+      value: 46.926
+    - type: mrr_at_100
+      value: 47.815000000000005
+    - type: mrr_at_1000
+      value: 47.849000000000004
+    - type: mrr_at_3
+      value: 44.273
+    - type: mrr_at_5
+      value: 45.774
+    - type: ndcg_at_1
+      value: 35.046
+    - type: ndcg_at_10
+      value: 48.937000000000005
+    - type: ndcg_at_100
+      value: 54.544000000000004
+    - type: ndcg_at_1000
+      value: 56.069
+    - type: ndcg_at_3
+      value: 42.858000000000004
+    - type: ndcg_at_5
+      value: 45.644
+    - type: precision_at_1
+      value: 35.046
+    - type: precision_at_10
+      value: 9.452
+    - type: precision_at_100
+      value: 1.429
+    - type: precision_at_1000
+      value: 0.173
+    - type: precision_at_3
+      value: 21.346999999999998
+    - type: precision_at_5
+      value: 15.342
+    - type: recall_at_1
+      value: 28.038999999999998
+    - type: recall_at_10
+      value: 64.59700000000001
+    - type: recall_at_100
+      value: 87.735
+    - type: recall_at_1000
+      value: 97.41300000000001
+    - type: recall_at_3
+      value: 47.368
+    - type: recall_at_5
+      value: 54.93900000000001
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
+    metrics:
+    - type: map_at_1
+      value: 28.17291666666667
+    - type: map_at_10
+      value: 40.025749999999995
+    - type: map_at_100
+      value: 41.39208333333333
+    - type: map_at_1000
+      value: 41.499249999999996
+    - type: map_at_3
+      value: 36.347
+    - type: map_at_5
+      value: 38.41391666666667
+    - type: mrr_at_1
+      value: 33.65925
+    - type: mrr_at_10
+      value: 44.085499999999996
+    - type: mrr_at_100
+      value: 44.94116666666667
+    - type: mrr_at_1000
+      value: 44.9855
+    - type: mrr_at_3
+      value: 41.2815
+    - type: mrr_at_5
+      value: 42.91491666666666
+    - type: ndcg_at_1
+      value: 33.65925
+    - type: ndcg_at_10
+      value: 46.430833333333325
+    - type: ndcg_at_100
+      value: 51.761
+    - type: ndcg_at_1000
+      value: 53.50899999999999
+    - type: ndcg_at_3
+      value: 40.45133333333333
+    - type: ndcg_at_5
+      value: 43.31483333333334
+    - type: precision_at_1
+      value: 33.65925
+    - type: precision_at_10
+      value: 8.4995
+    - type: precision_at_100
+      value: 1.3210000000000004
+    - type: precision_at_1000
+      value: 0.16591666666666666
+    - type: precision_at_3
+      value: 19.165083333333335
+    - type: precision_at_5
+      value: 13.81816666666667
+    - type: recall_at_1
+      value: 28.17291666666667
+    - type: recall_at_10
+      value: 61.12624999999999
+    - type: recall_at_100
+      value: 83.97266666666667
+    - type: recall_at_1000
+      value: 95.66550000000001
+    - type: recall_at_3
+      value: 44.661249999999995
+    - type: recall_at_5
+      value: 51.983333333333334
+    - type: map_at_1
+      value: 17.936
+    - type: map_at_10
+      value: 27.399
+    - type: map_at_100
+      value: 28.632
+    - type: map_at_1000
+      value: 28.738000000000003
+    - type: map_at_3
+      value: 24.456
+    - type: map_at_5
+      value: 26.06
+    - type: mrr_at_1
+      value: 19.224
+    - type: mrr_at_10
+      value: 28.998
+    - type: mrr_at_100
+      value: 30.11
+    - type: mrr_at_1000
+      value: 30.177
+    - type: mrr_at_3
+      value: 26.247999999999998
+    - type: mrr_at_5
+      value: 27.708
+    - type: ndcg_at_1
+      value: 19.224
+    - type: ndcg_at_10
+      value: 32.911
+    - type: ndcg_at_100
+      value: 38.873999999999995
+    - type: ndcg_at_1000
+      value: 41.277
+    - type: ndcg_at_3
+      value: 27.142
+    - type: ndcg_at_5
+      value: 29.755
+    - type: precision_at_1
+      value: 19.224
+    - type: precision_at_10
+      value: 5.6930000000000005
+    - type: precision_at_100
+      value: 0.9259999999999999
+    - type: precision_at_1000
+      value: 0.126
+    - type: precision_at_3
+      value: 12.138
+    - type: precision_at_5
+      value: 8.909
+    - type: recall_at_1
+      value: 17.936
+    - type: recall_at_10
+      value: 48.096
+    - type: recall_at_100
+      value: 75.389
+    - type: recall_at_1000
+      value: 92.803
+    - type: recall_at_3
+      value: 32.812999999999995
+    - type: recall_at_5
+      value: 38.851
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackStatsRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
+    metrics:
+    - type: map_at_1
+      value: 24.681
+    - type: map_at_10
+      value: 34.892
+    - type: map_at_100
+      value: 35.996
+    - type: map_at_1000
+      value: 36.083
+    - type: map_at_3
+      value: 31.491999999999997
+    - type: map_at_5
+      value: 33.632
+    - type: mrr_at_1
+      value: 28.528
+    - type: mrr_at_10
+      value: 37.694
+    - type: mrr_at_100
+      value: 38.613
+    - type: mrr_at_1000
+      value: 38.668
+    - type: mrr_at_3
+      value: 34.714
+    - type: mrr_at_5
+      value: 36.616
+    - type: ndcg_at_1
+      value: 28.528
+    - type: ndcg_at_10
+      value: 40.703
+    - type: ndcg_at_100
+      value: 45.993
+    - type: ndcg_at_1000
+      value: 47.847
+    - type: ndcg_at_3
+      value: 34.622
+    - type: ndcg_at_5
+      value: 38.035999999999994
+    - type: precision_at_1
+      value: 28.528
+    - type: precision_at_10
+      value: 6.902
+    - type: precision_at_100
+      value: 1.0370000000000001
+    - type: precision_at_1000
+      value: 0.126
+    - type: precision_at_3
+      value: 15.798000000000002
+    - type: precision_at_5
+      value: 11.655999999999999
+    - type: recall_at_1
+      value: 24.681
+    - type: recall_at_10
+      value: 55.81
+    - type: recall_at_100
+      value: 79.785
+    - type: recall_at_1000
+      value: 92.959
+    - type: recall_at_3
+      value: 39.074
+    - type: recall_at_5
+      value: 47.568
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackTexRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 46989137a86843e03a6195de44b09deda022eec7
+    metrics:
+    - type: map_at_1
+      value: 18.627
+    - type: map_at_10
+      value: 27.872000000000003
+    - type: map_at_100
+      value: 29.237999999999996
+    - type: map_at_1000
+      value: 29.363
+    - type: map_at_3
+      value: 24.751
+    - type: map_at_5
+      value: 26.521
+    - type: mrr_at_1
+      value: 23.021
+    - type: mrr_at_10
+      value: 31.924000000000003
+    - type: mrr_at_100
+      value: 32.922000000000004
+    - type: mrr_at_1000
+      value: 32.988
+    - type: mrr_at_3
+      value: 29.192
+    - type: mrr_at_5
+      value: 30.798
+    - type: ndcg_at_1
+      value: 23.021
+    - type: ndcg_at_10
+      value: 33.535
+    - type: ndcg_at_100
+      value: 39.732
+    - type: ndcg_at_1000
+      value: 42.201
+    - type: ndcg_at_3
+      value: 28.153
+    - type: ndcg_at_5
+      value: 30.746000000000002
+    - type: precision_at_1
+      value: 23.021
+    - type: precision_at_10
+      value: 6.459
+    - type: precision_at_100
+      value: 1.1320000000000001
+    - type: precision_at_1000
+      value: 0.153
+    - type: precision_at_3
+      value: 13.719000000000001
+    - type: precision_at_5
+      value: 10.193000000000001
+    - type: recall_at_1
+      value: 18.627
+    - type: recall_at_10
+      value: 46.463
+    - type: recall_at_100
+      value: 74.226
+    - type: recall_at_1000
+      value: 91.28500000000001
+    - type: recall_at_3
+      value: 31.357000000000003
+    - type: recall_at_5
+      value: 38.067
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackUnixRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
+    metrics:
+    - type: map_at_1
+      value: 31.457
+    - type: map_at_10
+      value: 42.888
+    - type: map_at_100
+      value: 44.24
+    - type: map_at_1000
+      value: 44.327
+    - type: map_at_3
+      value: 39.588
+    - type: map_at_5
+      value: 41.423
+    - type: mrr_at_1
+      value: 37.126999999999995
+    - type: mrr_at_10
+      value: 47.083000000000006
+    - type: mrr_at_100
+      value: 47.997
+    - type: mrr_at_1000
+      value: 48.044
+    - type: mrr_at_3
+      value: 44.574000000000005
+    - type: mrr_at_5
+      value: 46.202
+    - type: ndcg_at_1
+      value: 37.126999999999995
+    - type: ndcg_at_10
+      value: 48.833
+    - type: ndcg_at_100
+      value: 54.327000000000005
+    - type: ndcg_at_1000
+      value: 56.011
+    - type: ndcg_at_3
+      value: 43.541999999999994
+    - type: ndcg_at_5
+      value: 46.127
+    - type: precision_at_1
+      value: 37.126999999999995
+    - type: precision_at_10
+      value: 8.376999999999999
+    - type: precision_at_100
+      value: 1.2309999999999999
+    - type: precision_at_1000
+      value: 0.146
+    - type: precision_at_3
+      value: 20.211000000000002
+    - type: precision_at_5
+      value: 14.16
+    - type: recall_at_1
+      value: 31.457
+    - type: recall_at_10
+      value: 62.369
+    - type: recall_at_100
+      value: 85.444
+    - type: recall_at_1000
+      value: 96.65599999999999
+    - type: recall_at_3
+      value: 47.961
+    - type: recall_at_5
+      value: 54.676
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackWebmastersRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
+    metrics:
+    - type: map_at_1
+      value: 27.139999999999997
+    - type: map_at_10
+      value: 38.801
+    - type: map_at_100
+      value: 40.549
+    - type: map_at_1000
+      value: 40.802
+    - type: map_at_3
+      value: 35.05
+    - type: map_at_5
+      value: 36.884
+    - type: mrr_at_1
+      value: 33.004
+    - type: mrr_at_10
+      value: 43.864
+    - type: mrr_at_100
+      value: 44.667
+    - type: mrr_at_1000
+      value: 44.717
+    - type: mrr_at_3
+      value: 40.777
+    - type: mrr_at_5
+      value: 42.319
+    - type: ndcg_at_1
+      value: 33.004
+    - type: ndcg_at_10
+      value: 46.022
+    - type: ndcg_at_100
+      value: 51.542
+    - type: ndcg_at_1000
+      value: 53.742000000000004
+    - type: ndcg_at_3
+      value: 39.795
+    - type: ndcg_at_5
+      value: 42.272
+    - type: precision_at_1
+      value: 33.004
+    - type: precision_at_10
+      value: 9.012
+    - type: precision_at_100
+      value: 1.7770000000000001
+    - type: precision_at_1000
+      value: 0.26
+    - type: precision_at_3
+      value: 19.038
+    - type: precision_at_5
+      value: 13.675999999999998
+    - type: recall_at_1
+      value: 27.139999999999997
+    - type: recall_at_10
+      value: 60.961
+    - type: recall_at_100
+      value: 84.451
+    - type: recall_at_1000
+      value: 98.113
+    - type: recall_at_3
+      value: 43.001
+    - type: recall_at_5
+      value: 49.896
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB ClimateFEVER
+      type: mteb/climate-fever
+      config: default
+      split: test
+      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
+    metrics:
+    - type: map_at_1
+      value: 22.076999999999998
+    - type: map_at_10
+      value: 35.44
+    - type: map_at_100
+      value: 37.651
+    - type: map_at_1000
+      value: 37.824999999999996
+    - type: map_at_3
+      value: 30.764999999999997
+    - type: map_at_5
+      value: 33.26
+    - type: mrr_at_1
+      value: 50.163000000000004
+    - type: mrr_at_10
+      value: 61.207
+    - type: mrr_at_100
+      value: 61.675000000000004
+    - type: mrr_at_1000
+      value: 61.692
+    - type: mrr_at_3
+      value: 58.60999999999999
+    - type: mrr_at_5
+      value: 60.307
+    - type: ndcg_at_1
+      value: 50.163000000000004
+    - type: ndcg_at_10
+      value: 45.882
+    - type: ndcg_at_100
+      value: 53.239999999999995
+    - type: ndcg_at_1000
+      value: 55.852000000000004
+    - type: ndcg_at_3
+      value: 40.514
+    - type: ndcg_at_5
+      value: 42.038
+    - type: precision_at_1
+      value: 50.163000000000004
+    - type: precision_at_10
+      value: 13.466000000000001
+    - type: precision_at_100
+      value: 2.164
+    - type: precision_at_1000
+      value: 0.266
+    - type: precision_at_3
+      value: 29.707
+    - type: precision_at_5
+      value: 21.694
+    - type: recall_at_1
+      value: 22.076999999999998
+    - type: recall_at_10
+      value: 50.193
+    - type: recall_at_100
+      value: 74.993
+    - type: recall_at_1000
+      value: 89.131
+    - type: recall_at_3
+      value: 35.472
+    - type: recall_at_5
+      value: 41.814
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB DBPedia
+      type: mteb/dbpedia
+      config: default
+      split: test
+      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
+    metrics:
+    - type: map_at_1
+      value: 9.953
+    - type: map_at_10
+      value: 24.515
+    - type: map_at_100
+      value: 36.173
+    - type: map_at_1000
+      value: 38.351
+    - type: map_at_3
+      value: 16.592000000000002
+    - type: map_at_5
+      value: 20.036
+    - type: mrr_at_1
+      value: 74.25
+    - type: mrr_at_10
+      value: 81.813
+    - type: mrr_at_100
+      value: 82.006
+    - type: mrr_at_1000
+      value: 82.011
+    - type: mrr_at_3
+      value: 80.875
+    - type: mrr_at_5
+      value: 81.362
+    - type: ndcg_at_1
+      value: 62.5
+    - type: ndcg_at_10
+      value: 52.42
+    - type: ndcg_at_100
+      value: 56.808
+    - type: ndcg_at_1000
+      value: 63.532999999999994
+    - type: ndcg_at_3
+      value: 56.654
+    - type: ndcg_at_5
+      value: 54.18300000000001
+    - type: precision_at_1
+      value: 74.25
+    - type: precision_at_10
+      value: 42.699999999999996
+    - type: precision_at_100
+      value: 13.675
+    - type: precision_at_1000
+      value: 2.664
+    - type: precision_at_3
+      value: 60.5
+    - type: precision_at_5
+      value: 52.800000000000004
+    - type: recall_at_1
+      value: 9.953
+    - type: recall_at_10
+      value: 30.253999999999998
+    - type: recall_at_100
+      value: 62.516000000000005
+    - type: recall_at_1000
+      value: 84.163
+    - type: recall_at_3
+      value: 18.13
+    - type: recall_at_5
+      value: 22.771
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB EmotionClassification
+      type: mteb/emotion
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 79.455
+    - type: f1
+      value: 74.16798697647569
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB FEVER
+      type: mteb/fever
+      config: default
+      split: test
+      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
+    metrics:
+    - type: map_at_1
+      value: 87.531
+    - type: map_at_10
+      value: 93.16799999999999
+    - type: map_at_100
+      value: 93.341
+    - type: map_at_1000
+      value: 93.349
+    - type: map_at_3
+      value: 92.444
+    - type: map_at_5
+      value: 92.865
+    - type: mrr_at_1
+      value: 94.014
+    - type: mrr_at_10
+      value: 96.761
+    - type: mrr_at_100
+      value: 96.762
+    - type: mrr_at_1000
+      value: 96.762
+    - type: mrr_at_3
+      value: 96.672
+    - type: mrr_at_5
+      value: 96.736
+    - type: ndcg_at_1
+      value: 94.014
+    - type: ndcg_at_10
+      value: 95.112
+    - type: ndcg_at_100
+      value: 95.578
+    - type: ndcg_at_1000
+      value: 95.68900000000001
+    - type: ndcg_at_3
+      value: 94.392
+    - type: ndcg_at_5
+      value: 94.72500000000001
+    - type: precision_at_1
+      value: 94.014
+    - type: precision_at_10
+      value: 11.065
+    - type: precision_at_100
+      value: 1.157
+    - type: precision_at_1000
+      value: 0.11800000000000001
+    - type: precision_at_3
+      value: 35.259
+    - type: precision_at_5
+      value: 21.599
+    - type: recall_at_1
+      value: 87.531
+    - type: recall_at_10
+      value: 97.356
+    - type: recall_at_100
+      value: 98.965
+    - type: recall_at_1000
+      value: 99.607
+    - type: recall_at_3
+      value: 95.312
+    - type: recall_at_5
+      value: 96.295
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB FiQA2018
+      type: mteb/fiqa
+      config: default
+      split: test
+      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
+    metrics:
+    - type: map_at_1
+      value: 32.055
+    - type: map_at_10
+      value: 53.114
+    - type: map_at_100
+      value: 55.235
+    - type: map_at_1000
+      value: 55.345
+    - type: map_at_3
+      value: 45.854
+    - type: map_at_5
+      value: 50.025
+    - type: mrr_at_1
+      value: 60.34
+    - type: mrr_at_10
+      value: 68.804
+    - type: mrr_at_100
+      value: 69.309
+    - type: mrr_at_1000
+      value: 69.32199999999999
+    - type: mrr_at_3
+      value: 66.40899999999999
+    - type: mrr_at_5
+      value: 67.976
+    - type: ndcg_at_1
+      value: 60.34
+    - type: ndcg_at_10
+      value: 62.031000000000006
+    - type: ndcg_at_100
+      value: 68.00500000000001
+    - type: ndcg_at_1000
+      value: 69.286
+    - type: ndcg_at_3
+      value: 56.355999999999995
+    - type: ndcg_at_5
+      value: 58.687
+    - type: precision_at_1
+      value: 60.34
+    - type: precision_at_10
+      value: 17.176
+    - type: precision_at_100
+      value: 2.36
+    - type: precision_at_1000
+      value: 0.259
+    - type: precision_at_3
+      value: 37.14
+    - type: precision_at_5
+      value: 27.809
+    - type: recall_at_1
+      value: 32.055
+    - type: recall_at_10
+      value: 70.91
+    - type: recall_at_100
+      value: 91.83
+    - type: recall_at_1000
+      value: 98.871
+    - type: recall_at_3
+      value: 51.202999999999996
+    - type: recall_at_5
+      value: 60.563
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB HotpotQA
+      type: mteb/hotpotqa
+      config: default
+      split: test
+      revision: ab518f4d6fcca38d87c25209f94beba119d02014
+    metrics:
+    - type: map_at_1
+      value: 43.68
+    - type: map_at_10
+      value: 64.389
+    - type: map_at_100
+      value: 65.24
+    - type: map_at_1000
+      value: 65.303
+    - type: map_at_3
+      value: 61.309000000000005
+    - type: map_at_5
+      value: 63.275999999999996
+    - type: mrr_at_1
+      value: 87.36
+    - type: mrr_at_10
+      value: 91.12
+    - type: mrr_at_100
+      value: 91.227
+    - type: mrr_at_1000
+      value: 91.229
+    - type: mrr_at_3
+      value: 90.57600000000001
+    - type: mrr_at_5
+      value: 90.912
+    - type: ndcg_at_1
+      value: 87.36
+    - type: ndcg_at_10
+      value: 73.076
+    - type: ndcg_at_100
+      value: 75.895
+    - type: ndcg_at_1000
+      value: 77.049
+    - type: ndcg_at_3
+      value: 68.929
+    - type: ndcg_at_5
+      value: 71.28
+    - type: precision_at_1
+      value: 87.36
+    - type: precision_at_10
+      value: 14.741000000000001
+    - type: precision_at_100
+      value: 1.694
+    - type: precision_at_1000
+      value: 0.185
+    - type: precision_at_3
+      value: 43.043
+    - type: precision_at_5
+      value: 27.681
+    - type: recall_at_1
+      value: 43.68
+    - type: recall_at_10
+      value: 73.707
+    - type: recall_at_100
+      value: 84.7
+    - type: recall_at_1000
+      value: 92.309
+    - type: recall_at_3
+      value: 64.564
+    - type: recall_at_5
+      value: 69.203
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB ImdbClassification
+      type: mteb/imdb
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 96.75399999999999
+    - type: ap
+      value: 95.29389839242187
+    - type: f1
+      value: 96.75348377433475
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB MSMARCO
+      type: mteb/msmarco
+      config: default
+      split: dev
+      revision: c5a29a104738b98a9e76336939199e264163d4a0
+    metrics:
+    - type: map_at_1
+      value: 25.176
+    - type: map_at_10
+      value: 38.598
+    - type: map_at_100
+      value: 39.707
+    - type: map_at_1000
+      value: 39.744
+    - type: map_at_3
+      value: 34.566
+    - type: map_at_5
+      value: 36.863
+    - type: mrr_at_1
+      value: 25.874000000000002
+    - type: mrr_at_10
+      value: 39.214
+    - type: mrr_at_100
+      value: 40.251
+    - type: mrr_at_1000
+      value: 40.281
+    - type: mrr_at_3
+      value: 35.291
+    - type: mrr_at_5
+      value: 37.545
+    - type: ndcg_at_1
+      value: 25.874000000000002
+    - type: ndcg_at_10
+      value: 45.98
+    - type: ndcg_at_100
+      value: 51.197
+    - type: ndcg_at_1000
+      value: 52.073
+    - type: ndcg_at_3
+      value: 37.785999999999994
+    - type: ndcg_at_5
+      value: 41.870000000000005
+    - type: precision_at_1
+      value: 25.874000000000002
+    - type: precision_at_10
+      value: 7.181
+    - type: precision_at_100
+      value: 0.979
+    - type: precision_at_1000
+      value: 0.106
+    - type: precision_at_3
+      value: 16.051000000000002
+    - type: precision_at_5
+      value: 11.713
+    - type: recall_at_1
+      value: 25.176
+    - type: recall_at_10
+      value: 68.67699999999999
+    - type: recall_at_100
+      value: 92.55
+    - type: recall_at_1000
+      value: 99.164
+    - type: recall_at_3
+      value: 46.372
+    - type: recall_at_5
+      value: 56.16
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MTOPDomainClassification (en)
+      type: mteb/mtop_domain
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 99.03784769721841
+    - type: f1
+      value: 98.97791641821495
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MTOPIntentClassification (en)
+      type: mteb/mtop_intent
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 91.88326493388054
+    - type: f1
+      value: 73.74809928034335
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveIntentClassification (en)
+      type: mteb/amazon_massive_intent
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 85.41358439811701
+    - type: f1
+      value: 83.503679460639
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveScenarioClassification (en)
+      type: mteb/amazon_massive_scenario
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 89.77135171486215
+    - type: f1
+      value: 88.89843747468366
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB MedrxivClusteringP2P
+      type: mteb/medrxiv-clustering-p2p
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 46.22695362087359
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB MedrxivClusteringS2S
+      type: mteb/medrxiv-clustering-s2s
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 44.132372165849425
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB MindSmallReranking
+      type: mteb/mind_small
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 33.35680810650402
+    - type: mrr
+      value: 34.72625715637218
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB NFCorpus
+      type: mteb/nfcorpus
+      config: default
+      split: test
+      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
+    metrics:
+    - type: map_at_1
+      value: 7.165000000000001
+    - type: map_at_10
+      value: 15.424
+    - type: map_at_100
+      value: 20.28
+    - type: map_at_1000
+      value: 22.065
+    - type: map_at_3
+      value: 11.236
+    - type: map_at_5
+      value: 13.025999999999998
+    - type: mrr_at_1
+      value: 51.702999999999996
+    - type: mrr_at_10
+      value: 59.965
+    - type: mrr_at_100
+      value: 60.667
+    - type: mrr_at_1000
+      value: 60.702999999999996
+    - type: mrr_at_3
+      value: 58.772000000000006
+    - type: mrr_at_5
+      value: 59.267
+    - type: ndcg_at_1
+      value: 49.536
+    - type: ndcg_at_10
+      value: 40.6
+    - type: ndcg_at_100
+      value: 37.848
+    - type: ndcg_at_1000
+      value: 46.657
+    - type: ndcg_at_3
+      value: 46.117999999999995
+    - type: ndcg_at_5
+      value: 43.619
+    - type: precision_at_1
+      value: 51.393
+    - type: precision_at_10
+      value: 30.31
+    - type: precision_at_100
+      value: 9.972
+    - type: precision_at_1000
+      value: 2.329
+    - type: precision_at_3
+      value: 43.137
+    - type: precision_at_5
+      value: 37.585
+    - type: recall_at_1
+      value: 7.165000000000001
+    - type: recall_at_10
+      value: 19.689999999999998
+    - type: recall_at_100
+      value: 39.237
+    - type: recall_at_1000
+      value: 71.417
+    - type: recall_at_3
+      value: 12.247
+    - type: recall_at_5
+      value: 14.902999999999999
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB NQ
+      type: mteb/nq
+      config: default
+      split: test
+      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
+    metrics:
+    - type: map_at_1
+      value: 42.653999999999996
+    - type: map_at_10
+      value: 59.611999999999995
+    - type: map_at_100
+      value: 60.32300000000001
+    - type: map_at_1000
+      value: 60.336
+    - type: map_at_3
+      value: 55.584999999999994
+    - type: map_at_5
+      value: 58.19
+    - type: mrr_at_1
+      value: 47.683
+    - type: mrr_at_10
+      value: 62.06700000000001
+    - type: mrr_at_100
+      value: 62.537
+    - type: mrr_at_1000
+      value: 62.544999999999995
+    - type: mrr_at_3
+      value: 59.178
+    - type: mrr_at_5
+      value: 61.034
+    - type: ndcg_at_1
+      value: 47.654
+    - type: ndcg_at_10
+      value: 67.001
+    - type: ndcg_at_100
+      value: 69.73899999999999
+    - type: ndcg_at_1000
+      value: 69.986
+    - type: ndcg_at_3
+      value: 59.95700000000001
+    - type: ndcg_at_5
+      value: 64.025
+    - type: precision_at_1
+      value: 47.654
+    - type: precision_at_10
+      value: 10.367999999999999
+    - type: precision_at_100
+      value: 1.192
+    - type: precision_at_1000
+      value: 0.121
+    - type: precision_at_3
+      value: 26.651000000000003
+    - type: precision_at_5
+      value: 18.459
+    - type: recall_at_1
+      value: 42.653999999999996
+    - type: recall_at_10
+      value: 86.619
+    - type: recall_at_100
+      value: 98.04899999999999
+    - type: recall_at_1000
+      value: 99.812
+    - type: recall_at_3
+      value: 68.987
+    - type: recall_at_5
+      value: 78.158
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB QuoraRetrieval
+      type: mteb/quora
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 72.538
+    - type: map_at_10
+      value: 86.702
+    - type: map_at_100
+      value: 87.31
+    - type: map_at_1000
+      value: 87.323
+    - type: map_at_3
+      value: 83.87
+    - type: map_at_5
+      value: 85.682
+    - type: mrr_at_1
+      value: 83.31
+    - type: mrr_at_10
+      value: 89.225
+    - type: mrr_at_100
+      value: 89.30399999999999
+    - type: mrr_at_1000
+      value: 89.30399999999999
+    - type: mrr_at_3
+      value: 88.44300000000001
+    - type: mrr_at_5
+      value: 89.005
+    - type: ndcg_at_1
+      value: 83.32000000000001
+    - type: ndcg_at_10
+      value: 90.095
+    - type: ndcg_at_100
+      value: 91.12
+    - type: ndcg_at_1000
+      value: 91.179
+    - type: ndcg_at_3
+      value: 87.606
+    - type: ndcg_at_5
+      value: 89.031
+    - type: precision_at_1
+      value: 83.32000000000001
+    - type: precision_at_10
+      value: 13.641
+    - type: precision_at_100
+      value: 1.541
+    - type: precision_at_1000
+      value: 0.157
+    - type: precision_at_3
+      value: 38.377
+    - type: precision_at_5
+      value: 25.162000000000003
+    - type: recall_at_1
+      value: 72.538
+    - type: recall_at_10
+      value: 96.47200000000001
+    - type: recall_at_100
+      value: 99.785
+    - type: recall_at_1000
+      value: 99.99900000000001
+    - type: recall_at_3
+      value: 89.278
+    - type: recall_at_5
+      value: 93.367
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB RedditClustering
+      type: mteb/reddit-clustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 73.55219145406065
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB RedditClusteringP2P
+      type: mteb/reddit-clustering-p2p
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 74.13437105242755
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB SCIDOCS
+      type: mteb/scidocs
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 6.873
+    - type: map_at_10
+      value: 17.944
+    - type: map_at_100
+      value: 21.171
+    - type: map_at_1000
+      value: 21.528
+    - type: map_at_3
+      value: 12.415
+    - type: map_at_5
+      value: 15.187999999999999
+    - type: mrr_at_1
+      value: 33.800000000000004
+    - type: mrr_at_10
+      value: 46.455
+    - type: mrr_at_100
+      value: 47.378
+    - type: mrr_at_1000
+      value: 47.394999999999996
+    - type: mrr_at_3
+      value: 42.367
+    - type: mrr_at_5
+      value: 44.972
+    - type: ndcg_at_1
+      value: 33.800000000000004
+    - type: ndcg_at_10
+      value: 28.907
+    - type: ndcg_at_100
+      value: 39.695
+    - type: ndcg_at_1000
+      value: 44.582
+    - type: ndcg_at_3
+      value: 26.949
+    - type: ndcg_at_5
+      value: 23.988
+    - type: precision_at_1
+      value: 33.800000000000004
+    - type: precision_at_10
+      value: 15.079999999999998
+    - type: precision_at_100
+      value: 3.056
+    - type: precision_at_1000
+      value: 0.42100000000000004
+    - type: precision_at_3
+      value: 25.167
+    - type: precision_at_5
+      value: 21.26
+    - type: recall_at_1
+      value: 6.873
+    - type: recall_at_10
+      value: 30.568
+    - type: recall_at_100
+      value: 62.062
+    - type: recall_at_1000
+      value: 85.37700000000001
+    - type: recall_at_3
+      value: 15.312999999999999
+    - type: recall_at_5
+      value: 21.575
+  - task:
+      type: STS
+    dataset:
+      name: MTEB SICK-R
+      type: mteb/sickr-sts
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.37009118256057
+    - type: cos_sim_spearman
+      value: 79.27986395671529
+    - type: euclidean_pearson
+      value: 79.18037715442115
+    - type: euclidean_spearman
+      value: 79.28004791561621
+    - type: manhattan_pearson
+      value: 79.34062972800541
+    - type: manhattan_spearman
+      value: 79.43106695543402
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS12
+      type: mteb/sts12-sts
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.48474767383833
+    - type: cos_sim_spearman
+      value: 79.54505388752513
+    - type: euclidean_pearson
+      value: 83.43282704179565
+    - type: euclidean_spearman
+      value: 79.54579919925405
+    - type: manhattan_pearson
+      value: 83.77564492427952
+    - type: manhattan_spearman
+      value: 79.84558396989286
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS13
+      type: mteb/sts13-sts
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 88.803698035802
+    - type: cos_sim_spearman
+      value: 88.83451367754881
+    - type: euclidean_pearson
+      value: 88.28939285711628
+    - type: euclidean_spearman
+      value: 88.83528996073112
+    - type: manhattan_pearson
+      value: 88.28017412671795
+    - type: manhattan_spearman
+      value: 88.9228828016344
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS14
+      type: mteb/sts14-sts
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.27469288153428
+    - type: cos_sim_spearman
+      value: 83.87477064876288
+    - type: euclidean_pearson
+      value: 84.2601737035379
+    - type: euclidean_spearman
+      value: 83.87431082479074
+    - type: manhattan_pearson
+      value: 84.3621547772745
+    - type: manhattan_spearman
+      value: 84.12094375000423
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS15
+      type: mteb/sts15-sts
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 88.12749863201587
+    - type: cos_sim_spearman
+      value: 88.54287568368565
+    - type: euclidean_pearson
+      value: 87.90429700607999
+    - type: euclidean_spearman
+      value: 88.5437689576261
+    - type: manhattan_pearson
+      value: 88.19276653356833
+    - type: manhattan_spearman
+      value: 88.99995393814679
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS16
+      type: mteb/sts16-sts
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.68398747560902
+    - type: cos_sim_spearman
+      value: 86.48815303460574
+    - type: euclidean_pearson
+      value: 85.52356631237954
+    - type: euclidean_spearman
+      value: 86.486391949551
+    - type: manhattan_pearson
+      value: 85.67267981761788
+    - type: manhattan_spearman
+      value: 86.7073696332485
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS17 (en-en)
+      type: mteb/sts17-crosslingual-sts
+      config: en-en
+      split: test
+      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+    metrics:
+    - type: cos_sim_pearson
+      value: 88.9057107443124
+    - type: cos_sim_spearman
+      value: 88.7312168757697
+    - type: euclidean_pearson
+      value: 88.72810439714794
+    - type: euclidean_spearman
+      value: 88.71976185854771
+    - type: manhattan_pearson
+      value: 88.50433745949111
+    - type: manhattan_spearman
+      value: 88.51726175544195
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS22 (en)
+      type: mteb/sts22-crosslingual-sts
+      config: en
+      split: test
+      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
+    metrics:
+    - type: cos_sim_pearson
+      value: 67.59391795109886
+    - type: cos_sim_spearman
+      value: 66.87613008631367
+    - type: euclidean_pearson
+      value: 69.23198488262217
+    - type: euclidean_spearman
+      value: 66.85427723013692
+    - type: manhattan_pearson
+      value: 69.50730124841084
+    - type: manhattan_spearman
+      value: 67.10404669820792
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STSBenchmark
+      type: mteb/stsbenchmark-sts
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.0820605344619
+    - type: cos_sim_spearman
+      value: 86.8518089863434
+    - type: euclidean_pearson
+      value: 86.31087134689284
+    - type: euclidean_spearman
+      value: 86.8518520517941
+    - type: manhattan_pearson
+      value: 86.47203796160612
+    - type: manhattan_spearman
+      value: 87.1080149734421
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB SciDocsRR
+      type: mteb/scidocs-reranking
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 89.09255369305481
+    - type: mrr
+      value: 97.10323445617563
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB SciFact
+      type: mteb/scifact
+      config: default
+      split: test
+      revision: 0228b52cf27578f30900b9e5271d331663a030d7
+    metrics:
+    - type: map_at_1
+      value: 61.260999999999996
+    - type: map_at_10
+      value: 74.043
+    - type: map_at_100
+      value: 74.37700000000001
+    - type: map_at_1000
+      value: 74.384
+    - type: map_at_3
+      value: 71.222
+    - type: map_at_5
+      value: 72.875
+    - type: mrr_at_1
+      value: 64.333
+    - type: mrr_at_10
+      value: 74.984
+    - type: mrr_at_100
+      value: 75.247
+    - type: mrr_at_1000
+      value: 75.25500000000001
+    - type: mrr_at_3
+      value: 73.167
+    - type: mrr_at_5
+      value: 74.35000000000001
+    - type: ndcg_at_1
+      value: 64.333
+    - type: ndcg_at_10
+      value: 79.06
+    - type: ndcg_at_100
+      value: 80.416
+    - type: ndcg_at_1000
+      value: 80.55600000000001
+    - type: ndcg_at_3
+      value: 74.753
+    - type: ndcg_at_5
+      value: 76.97500000000001
+    - type: precision_at_1
+      value: 64.333
+    - type: precision_at_10
+      value: 10.567
+    - type: precision_at_100
+      value: 1.1199999999999999
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 29.889
+    - type: precision_at_5
+      value: 19.533
+    - type: recall_at_1
+      value: 61.260999999999996
+    - type: recall_at_10
+      value: 93.167
+    - type: recall_at_100
+      value: 99.0
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 81.667
+    - type: recall_at_5
+      value: 87.394
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB SprintDuplicateQuestions
+      type: mteb/sprintduplicatequestions-pairclassification
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.71980198019801
+    - type: cos_sim_ap
+      value: 92.81616007802704
+    - type: cos_sim_f1
+      value: 85.17548454688318
+    - type: cos_sim_precision
+      value: 89.43894389438944
+    - type: cos_sim_recall
+      value: 81.3
+    - type: dot_accuracy
+      value: 99.71980198019801
+    - type: dot_ap
+      value: 92.81398760591358
+    - type: dot_f1
+      value: 85.17548454688318
+    - type: dot_precision
+      value: 89.43894389438944
+    - type: dot_recall
+      value: 81.3
+    - type: euclidean_accuracy
+      value: 99.71980198019801
+    - type: euclidean_ap
+      value: 92.81560637245072
+    - type: euclidean_f1
+      value: 85.17548454688318
+    - type: euclidean_precision
+      value: 89.43894389438944
+    - type: euclidean_recall
+      value: 81.3
+    - type: manhattan_accuracy
+      value: 99.73069306930694
+    - type: manhattan_ap
+      value: 93.14005487480794
+    - type: manhattan_f1
+      value: 85.56263269639068
+    - type: manhattan_precision
+      value: 91.17647058823529
+    - type: manhattan_recall
+      value: 80.60000000000001
+    - type: max_accuracy
+      value: 99.73069306930694
+    - type: max_ap
+      value: 93.14005487480794
+    - type: max_f1
+      value: 85.56263269639068
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB StackExchangeClustering
+      type: mteb/stackexchange-clustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 79.86443362395185
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB StackExchangeClusteringP2P
+      type: mteb/stackexchange-clustering-p2p
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 49.40897096662564
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB StackOverflowDupQuestions
+      type: mteb/stackoverflowdupquestions-reranking
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 55.66040806627947
+    - type: mrr
+      value: 56.58670475766064
+  - task:
+      type: Summarization
+    dataset:
+      name: MTEB SummEval
+      type: mteb/summeval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 31.51015090598575
+    - type: cos_sim_spearman
+      value: 31.35016454939226
+    - type: dot_pearson
+      value: 31.5150068731
+    - type: dot_spearman
+      value: 31.34790869023487
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB TRECCOVID
+      type: mteb/trec-covid
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.254
+    - type: map_at_10
+      value: 2.064
+    - type: map_at_100
+      value: 12.909
+    - type: map_at_1000
+      value: 31.761
+    - type: map_at_3
+      value: 0.738
+    - type: map_at_5
+      value: 1.155
+    - type: mrr_at_1
+      value: 96.0
+    - type: mrr_at_10
+      value: 98.0
+    - type: mrr_at_100
+      value: 98.0
+    - type: mrr_at_1000
+      value: 98.0
+    - type: mrr_at_3
+      value: 98.0
+    - type: mrr_at_5
+      value: 98.0
+    - type: ndcg_at_1
+      value: 93.0
+    - type: ndcg_at_10
+      value: 82.258
+    - type: ndcg_at_100
+      value: 64.34
+    - type: ndcg_at_1000
+      value: 57.912
+    - type: ndcg_at_3
+      value: 90.827
+    - type: ndcg_at_5
+      value: 86.79
+    - type: precision_at_1
+      value: 96.0
+    - type: precision_at_10
+      value: 84.8
+    - type: precision_at_100
+      value: 66.0
+    - type: precision_at_1000
+      value: 25.356
+    - type: precision_at_3
+      value: 94.667
+    - type: precision_at_5
+      value: 90.4
+    - type: recall_at_1
+      value: 0.254
+    - type: recall_at_10
+      value: 2.1950000000000003
+    - type: recall_at_100
+      value: 16.088
+    - type: recall_at_1000
+      value: 54.559000000000005
+    - type: recall_at_3
+      value: 0.75
+    - type: recall_at_5
+      value: 1.191
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB Touche2020
+      type: mteb/touche2020
+      config: default
+      split: test
+      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
+    metrics:
+    - type: map_at_1
+      value: 2.976
+    - type: map_at_10
+      value: 11.389000000000001
+    - type: map_at_100
+      value: 18.429000000000002
+    - type: map_at_1000
+      value: 20.113
+    - type: map_at_3
+      value: 6.483
+    - type: map_at_5
+      value: 8.770999999999999
+    - type: mrr_at_1
+      value: 40.816
+    - type: mrr_at_10
+      value: 58.118
+    - type: mrr_at_100
+      value: 58.489999999999995
+    - type: mrr_at_1000
+      value: 58.489999999999995
+    - type: mrr_at_3
+      value: 53.061
+    - type: mrr_at_5
+      value: 57.041
+    - type: ndcg_at_1
+      value: 40.816
+    - type: ndcg_at_10
+      value: 30.567
+    - type: ndcg_at_100
+      value: 42.44
+    - type: ndcg_at_1000
+      value: 53.480000000000004
+    - type: ndcg_at_3
+      value: 36.016
+    - type: ndcg_at_5
+      value: 34.257
+    - type: precision_at_1
+      value: 42.857
+    - type: precision_at_10
+      value: 25.714
+    - type: precision_at_100
+      value: 8.429
+    - type: precision_at_1000
+      value: 1.5939999999999999
+    - type: precision_at_3
+      value: 36.735
+    - type: precision_at_5
+      value: 33.878
+    - type: recall_at_1
+      value: 2.976
+    - type: recall_at_10
+      value: 17.854999999999997
+    - type: recall_at_100
+      value: 51.833
+    - type: recall_at_1000
+      value: 86.223
+    - type: recall_at_3
+      value: 7.887
+    - type: recall_at_5
+      value: 12.026
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB ToxicConversationsClassification
+      type: mteb/toxic_conversations_50k
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 85.1174
+    - type: ap
+      value: 30.169441069345748
+    - type: f1
+      value: 69.79254701873245
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB TweetSentimentExtractionClassification
+      type: mteb/tweet_sentiment_extraction
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 72.58347481607245
+    - type: f1
+      value: 72.74877295564937
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB TwentyNewsgroupsClustering
+      type: mteb/twentynewsgroups-clustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 53.90586138221305
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB TwitterSemEval2015
+      type: mteb/twittersemeval2015-pairclassification
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 87.35769207844072
+    - type: cos_sim_ap
+      value: 77.9645072410354
+    - type: cos_sim_f1
+      value: 71.32352941176471
+    - type: cos_sim_precision
+      value: 66.5903890160183
+    - type: cos_sim_recall
+      value: 76.78100263852242
+    - type: dot_accuracy
+      value: 87.37557370209214
+    - type: dot_ap
+      value: 77.96250046429908
+    - type: dot_f1
+      value: 71.28932757557064
+    - type: dot_precision
+      value: 66.95249130938586
+    - type: dot_recall
+      value: 76.22691292875989
+    - type: euclidean_accuracy
+      value: 87.35173153722357
+    - type: euclidean_ap
+      value: 77.96520460741593
+    - type: euclidean_f1
+      value: 71.32470733210104
+    - type: euclidean_precision
+      value: 66.91329479768785
+    - type: euclidean_recall
+      value: 76.35883905013192
+    - type: manhattan_accuracy
+      value: 87.25636287774931
+    - type: manhattan_ap
+      value: 77.77752485611796
+    - type: manhattan_f1
+      value: 71.18148599269183
+    - type: manhattan_precision
+      value: 66.10859728506787
+    - type: manhattan_recall
+      value: 77.0976253298153
+    - type: max_accuracy
+      value: 87.37557370209214
+    - type: max_ap
+      value: 77.96520460741593
+    - type: max_f1
+      value: 71.32470733210104
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB TwitterURLCorpus
+      type: mteb/twitterurlcorpus-pairclassification
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 89.38176737687739
+    - type: cos_sim_ap
+      value: 86.58811861657401
+    - type: cos_sim_f1
+      value: 79.09430644097604
+    - type: cos_sim_precision
+      value: 75.45085977911366
+    - type: cos_sim_recall
+      value: 83.10748383122882
+    - type: dot_accuracy
+      value: 89.38370784336554
+    - type: dot_ap
+      value: 86.58840606004333
+    - type: dot_f1
+      value: 79.10179860068133
+    - type: dot_precision
+      value: 75.44546153308643
+    - type: dot_recall
+      value: 83.13058207576223
+    - type: euclidean_accuracy
+      value: 89.38564830985369
+    - type: euclidean_ap
+      value: 86.58820721061164
+    - type: euclidean_f1
+      value: 79.09070942235888
+    - type: euclidean_precision
+      value: 75.38729937194697
+    - type: euclidean_recall
+      value: 83.17677856482906
+    - type: manhattan_accuracy
+      value: 89.40699344122326
+    - type: manhattan_ap
+      value: 86.60631843011362
+    - type: manhattan_f1
+      value: 79.14949970570925
+    - type: manhattan_precision
+      value: 75.78191039729502
+    - type: manhattan_recall
+      value: 82.83030489682784
+    - type: max_accuracy
+      value: 89.40699344122326
+    - type: max_ap
+      value: 86.60631843011362
+    - type: max_f1
+      value: 79.14949970570925
+  - task:
+      type: STS
+    dataset:
+      name: MTEB AFQMC
+      type: C-MTEB/AFQMC
+      config: default
+      split: validation
+      revision: b44c3b011063adb25877c13823db83bb193913c4
+    metrics:
+    - type: cos_sim_pearson
+      value: 65.58442135663871
+    - type: cos_sim_spearman
+      value: 72.2538631361313
+    - type: euclidean_pearson
+      value: 70.97255486607429
+    - type: euclidean_spearman
+      value: 72.25374250228647
+    - type: manhattan_pearson
+      value: 70.83250199989911
+    - type: manhattan_spearman
+      value: 72.14819496536272
+  - task:
+      type: STS
+    dataset:
+      name: MTEB ATEC
+      type: C-MTEB/ATEC
+      config: default
+      split: test
+      revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
+    metrics:
+    - type: cos_sim_pearson
+      value: 59.99478404929932
+    - type: cos_sim_spearman
+      value: 62.61836216999812
+    - type: euclidean_pearson
+      value: 66.86429811933593
+    - type: euclidean_spearman
+      value: 62.6183520374191
+    - type: manhattan_pearson
+      value: 66.8063778911633
+    - type: manhattan_spearman
+      value: 62.569607573241115
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonReviewsClassification (zh)
+      type: mteb/amazon_reviews_multi
+      config: zh
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 53.98400000000001
+    - type: f1
+      value: 51.21447361350723
+  - task:
+      type: STS
+    dataset:
+      name: MTEB BQ
+      type: C-MTEB/BQ
+      config: default
+      split: test
+      revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
+    metrics:
+    - type: cos_sim_pearson
+      value: 79.11941660686553
+    - type: cos_sim_spearman
+      value: 81.25029594540435
+    - type: euclidean_pearson
+      value: 82.06973504238826
+    - type: euclidean_spearman
+      value: 81.2501989488524
+    - type: manhattan_pearson
+      value: 82.10094630392753
+    - type: manhattan_spearman
+      value: 81.27987244392389
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB CLSClusteringP2P
+      type: C-MTEB/CLSClusteringP2P
+      config: default
+      split: test
+      revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
+    metrics:
+    - type: v_measure
+      value: 47.07270168705156
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB CLSClusteringS2S
+      type: C-MTEB/CLSClusteringS2S
+      config: default
+      split: test
+      revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
+    metrics:
+    - type: v_measure
+      value: 45.98511703185043
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB CMedQAv1
+      type: C-MTEB/CMedQAv1-reranking
+      config: default
+      split: test
+      revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
+    metrics:
+    - type: map
+      value: 88.19895157194931
+    - type: mrr
+      value: 90.21424603174603
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB CMedQAv2
+      type: C-MTEB/CMedQAv2-reranking
+      config: default
+      split: test
+      revision: 23d186750531a14a0357ca22cd92d712fd512ea0
+    metrics:
+    - type: map
+      value: 88.03317320980119
+    - type: mrr
+      value: 89.9461507936508
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CmedqaRetrieval
+      type: C-MTEB/CmedqaRetrieval
+      config: default
+      split: dev
+      revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
+    metrics:
+    - type: map_at_1
+      value: 29.037000000000003
+    - type: map_at_10
+      value: 42.001
+    - type: map_at_100
+      value: 43.773
+    - type: map_at_1000
+      value: 43.878
+    - type: map_at_3
+      value: 37.637
+    - type: map_at_5
+      value: 40.034
+    - type: mrr_at_1
+      value: 43.136
+    - type: mrr_at_10
+      value: 51.158
+    - type: mrr_at_100
+      value: 52.083
+    - type: mrr_at_1000
+      value: 52.12
+    - type: mrr_at_3
+      value: 48.733
+    - type: mrr_at_5
+      value: 50.025
+    - type: ndcg_at_1
+      value: 43.136
+    - type: ndcg_at_10
+      value: 48.685
+    - type: ndcg_at_100
+      value: 55.513
+    - type: ndcg_at_1000
+      value: 57.242000000000004
+    - type: ndcg_at_3
+      value: 43.329
+    - type: ndcg_at_5
+      value: 45.438
+    - type: precision_at_1
+      value: 43.136
+    - type: precision_at_10
+      value: 10.56
+    - type: precision_at_100
+      value: 1.6129999999999998
+    - type: precision_at_1000
+      value: 0.184
+    - type: precision_at_3
+      value: 24.064
+    - type: precision_at_5
+      value: 17.269000000000002
+    - type: recall_at_1
+      value: 29.037000000000003
+    - type: recall_at_10
+      value: 59.245000000000005
+    - type: recall_at_100
+      value: 87.355
+    - type: recall_at_1000
+      value: 98.74000000000001
+    - type: recall_at_3
+      value: 42.99
+    - type: recall_at_5
+      value: 49.681999999999995
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB Cmnli
+      type: C-MTEB/CMNLI
+      config: default
+      split: validation
+      revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
+    metrics:
+    - type: cos_sim_accuracy
+      value: 82.68190018039687
+    - type: cos_sim_ap
+      value: 90.18017125327886
+    - type: cos_sim_f1
+      value: 83.64080906868193
+    - type: cos_sim_precision
+      value: 79.7076890489303
+    - type: cos_sim_recall
+      value: 87.98223053542202
+    - type: dot_accuracy
+      value: 82.68190018039687
+    - type: dot_ap
+      value: 90.18782350103646
+    - type: dot_f1
+      value: 83.64242087729039
+    - type: dot_precision
+      value: 79.65313028764805
+    - type: dot_recall
+      value: 88.05237315875614
+    - type: euclidean_accuracy
+      value: 82.68190018039687
+    - type: euclidean_ap
+      value: 90.1801957900632
+    - type: euclidean_f1
+      value: 83.63636363636364
+    - type: euclidean_precision
+      value: 79.52772506852203
+    - type: euclidean_recall
+      value: 88.19265840542437
+    - type: manhattan_accuracy
+      value: 82.14070956103427
+    - type: manhattan_ap
+      value: 89.96178420101427
+    - type: manhattan_f1
+      value: 83.21087838578791
+    - type: manhattan_precision
+      value: 78.35605121850475
+    - type: manhattan_recall
+      value: 88.70703764320785
+    - type: max_accuracy
+      value: 82.68190018039687
+    - type: max_ap
+      value: 90.18782350103646
+    - type: max_f1
+      value: 83.64242087729039
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CovidRetrieval
+      type: C-MTEB/CovidRetrieval
+      config: default
+      split: dev
+      revision: 1271c7809071a13532e05f25fb53511ffce77117
+    metrics:
+    - type: map_at_1
+      value: 72.234
+    - type: map_at_10
+      value: 80.10000000000001
+    - type: map_at_100
+      value: 80.36
+    - type: map_at_1000
+      value: 80.363
+    - type: map_at_3
+      value: 78.315
+    - type: map_at_5
+      value: 79.607
+    - type: mrr_at_1
+      value: 72.392
+    - type: mrr_at_10
+      value: 80.117
+    - type: mrr_at_100
+      value: 80.36999999999999
+    - type: mrr_at_1000
+      value: 80.373
+    - type: mrr_at_3
+      value: 78.469
+    - type: mrr_at_5
+      value: 79.633
+    - type: ndcg_at_1
+      value: 72.392
+    - type: ndcg_at_10
+      value: 83.651
+    - type: ndcg_at_100
+      value: 84.749
+    - type: ndcg_at_1000
+      value: 84.83000000000001
+    - type: ndcg_at_3
+      value: 80.253
+    - type: ndcg_at_5
+      value: 82.485
+    - type: precision_at_1
+      value: 72.392
+    - type: precision_at_10
+      value: 9.557
+    - type: precision_at_100
+      value: 1.004
+    - type: precision_at_1000
+      value: 0.101
+    - type: precision_at_3
+      value: 28.732000000000003
+    - type: precision_at_5
+      value: 18.377
+    - type: recall_at_1
+      value: 72.234
+    - type: recall_at_10
+      value: 94.573
+    - type: recall_at_100
+      value: 99.368
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 85.669
+    - type: recall_at_5
+      value: 91.01700000000001
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB DuRetrieval
+      type: C-MTEB/DuRetrieval
+      config: default
+      split: dev
+      revision: a1a333e290fe30b10f3f56498e3a0d911a693ced
+    metrics:
+    - type: map_at_1
+      value: 26.173999999999996
+    - type: map_at_10
+      value: 80.04
+    - type: map_at_100
+      value: 82.94500000000001
+    - type: map_at_1000
+      value: 82.98100000000001
+    - type: map_at_3
+      value: 55.562999999999995
+    - type: map_at_5
+      value: 69.89800000000001
+    - type: mrr_at_1
+      value: 89.5
+    - type: mrr_at_10
+      value: 92.996
+    - type: mrr_at_100
+      value: 93.06400000000001
+    - type: mrr_at_1000
+      value: 93.065
+    - type: mrr_at_3
+      value: 92.658
+    - type: mrr_at_5
+      value: 92.84599999999999
+    - type: ndcg_at_1
+      value: 89.5
+    - type: ndcg_at_10
+      value: 87.443
+    - type: ndcg_at_100
+      value: 90.253
+    - type: ndcg_at_1000
+      value: 90.549
+    - type: ndcg_at_3
+      value: 85.874
+    - type: ndcg_at_5
+      value: 84.842
+    - type: precision_at_1
+      value: 89.5
+    - type: precision_at_10
+      value: 41.805
+    - type: precision_at_100
+      value: 4.827
+    - type: precision_at_1000
+      value: 0.49
+    - type: precision_at_3
+      value: 76.85
+    - type: precision_at_5
+      value: 64.8
+    - type: recall_at_1
+      value: 26.173999999999996
+    - type: recall_at_10
+      value: 89.101
+    - type: recall_at_100
+      value: 98.08099999999999
+    - type: recall_at_1000
+      value: 99.529
+    - type: recall_at_3
+      value: 57.902
+    - type: recall_at_5
+      value: 74.602
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB EcomRetrieval
+      type: C-MTEB/EcomRetrieval
+      config: default
+      split: dev
+      revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
+    metrics:
+    - type: map_at_1
+      value: 56.10000000000001
+    - type: map_at_10
+      value: 66.15299999999999
+    - type: map_at_100
+      value: 66.625
+    - type: map_at_1000
+      value: 66.636
+    - type: map_at_3
+      value: 63.632999999999996
+    - type: map_at_5
+      value: 65.293
+    - type: mrr_at_1
+      value: 56.10000000000001
+    - type: mrr_at_10
+      value: 66.15299999999999
+    - type: mrr_at_100
+      value: 66.625
+    - type: mrr_at_1000
+      value: 66.636
+    - type: mrr_at_3
+      value: 63.632999999999996
+    - type: mrr_at_5
+      value: 65.293
+    - type: ndcg_at_1
+      value: 56.10000000000001
+    - type: ndcg_at_10
+      value: 71.146
+    - type: ndcg_at_100
+      value: 73.27799999999999
+    - type: ndcg_at_1000
+      value: 73.529
+    - type: ndcg_at_3
+      value: 66.09
+    - type: ndcg_at_5
+      value: 69.08999999999999
+    - type: precision_at_1
+      value: 56.10000000000001
+    - type: precision_at_10
+      value: 8.68
+    - type: precision_at_100
+      value: 0.964
+    - type: precision_at_1000
+      value: 0.098
+    - type: precision_at_3
+      value: 24.4
+    - type: precision_at_5
+      value: 16.1
+    - type: recall_at_1
+      value: 56.10000000000001
+    - type: recall_at_10
+      value: 86.8
+    - type: recall_at_100
+      value: 96.39999999999999
+    - type: recall_at_1000
+      value: 98.3
+    - type: recall_at_3
+      value: 73.2
+    - type: recall_at_5
+      value: 80.5
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB IFlyTek
+      type: C-MTEB/IFlyTek-classification
+      config: default
+      split: validation
+      revision: 421605374b29664c5fc098418fe20ada9bd55f8a
+    metrics:
+    - type: accuracy
+      value: 54.52096960369373
+    - type: f1
+      value: 40.930845295808695
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB JDReview
+      type: C-MTEB/JDReview-classification
+      config: default
+      split: test
+      revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
+    metrics:
+    - type: accuracy
+      value: 86.51031894934334
+    - type: ap
+      value: 55.9516014323483
+    - type: f1
+      value: 81.54813679326381
+  - task:
+      type: STS
+    dataset:
+      name: MTEB LCQMC
+      type: C-MTEB/LCQMC
+      config: default
+      split: test
+      revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
+    metrics:
+    - type: cos_sim_pearson
+      value: 69.67437838574276
+    - type: cos_sim_spearman
+      value: 73.81314174653045
+    - type: euclidean_pearson
+      value: 72.63430276680275
+    - type: euclidean_spearman
+      value: 73.81358736777001
+    - type: manhattan_pearson
+      value: 72.58743833842829
+    - type: manhattan_spearman
+      value: 73.7590419009179
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB MMarcoReranking
+      type: C-MTEB/Mmarco-reranking
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map
+      value: 31.648613483640254
+    - type: mrr
+      value: 30.37420634920635
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB MMarcoRetrieval
+      type: C-MTEB/MMarcoRetrieval
+      config: default
+      split: dev
+      revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
+    metrics:
+    - type: map_at_1
+      value: 73.28099999999999
+    - type: map_at_10
+      value: 81.977
+    - type: map_at_100
+      value: 82.222
+    - type: map_at_1000
+      value: 82.22699999999999
+    - type: map_at_3
+      value: 80.441
+    - type: map_at_5
+      value: 81.46600000000001
+    - type: mrr_at_1
+      value: 75.673
+    - type: mrr_at_10
+      value: 82.41000000000001
+    - type: mrr_at_100
+      value: 82.616
+    - type: mrr_at_1000
+      value: 82.621
+    - type: mrr_at_3
+      value: 81.094
+    - type: mrr_at_5
+      value: 81.962
+    - type: ndcg_at_1
+      value: 75.673
+    - type: ndcg_at_10
+      value: 85.15599999999999
+    - type: ndcg_at_100
+      value: 86.151
+    - type: ndcg_at_1000
+      value: 86.26899999999999
+    - type: ndcg_at_3
+      value: 82.304
+    - type: ndcg_at_5
+      value: 84.009
+    - type: precision_at_1
+      value: 75.673
+    - type: precision_at_10
+      value: 10.042
+    - type: precision_at_100
+      value: 1.052
+    - type: precision_at_1000
+      value: 0.106
+    - type: precision_at_3
+      value: 30.673000000000002
+    - type: precision_at_5
+      value: 19.326999999999998
+    - type: recall_at_1
+      value: 73.28099999999999
+    - type: recall_at_10
+      value: 94.446
+    - type: recall_at_100
+      value: 98.737
+    - type: recall_at_1000
+      value: 99.649
+    - type: recall_at_3
+      value: 86.984
+    - type: recall_at_5
+      value: 91.024
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveIntentClassification (zh-CN)
+      type: mteb/amazon_massive_intent
+      config: zh-CN
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 81.08607935440484
+    - type: f1
+      value: 78.24879986066307
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveScenarioClassification (zh-CN)
+      type: mteb/amazon_massive_scenario
+      config: zh-CN
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 86.05917955615332
+    - type: f1
+      value: 85.05279279434997
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB MedicalRetrieval
+      type: C-MTEB/MedicalRetrieval
+      config: default
+      split: dev
+      revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
+    metrics:
+    - type: map_at_1
+      value: 56.2
+    - type: map_at_10
+      value: 62.57899999999999
+    - type: map_at_100
+      value: 63.154999999999994
+    - type: map_at_1000
+      value: 63.193
+    - type: map_at_3
+      value: 61.217
+    - type: map_at_5
+      value: 62.012
+    - type: mrr_at_1
+      value: 56.3
+    - type: mrr_at_10
+      value: 62.629000000000005
+    - type: mrr_at_100
+      value: 63.205999999999996
+    - type: mrr_at_1000
+      value: 63.244
+    - type: mrr_at_3
+      value: 61.267
+    - type: mrr_at_5
+      value: 62.062
+    - type: ndcg_at_1
+      value: 56.2
+    - type: ndcg_at_10
+      value: 65.592
+    - type: ndcg_at_100
+      value: 68.657
+    - type: ndcg_at_1000
+      value: 69.671
+    - type: ndcg_at_3
+      value: 62.808
+    - type: ndcg_at_5
+      value: 64.24499999999999
+    - type: precision_at_1
+      value: 56.2
+    - type: precision_at_10
+      value: 7.5
+    - type: precision_at_100
+      value: 0.899
+    - type: precision_at_1000
+      value: 0.098
+    - type: precision_at_3
+      value: 22.467000000000002
+    - type: precision_at_5
+      value: 14.180000000000001
+    - type: recall_at_1
+      value: 56.2
+    - type: recall_at_10
+      value: 75.0
+    - type: recall_at_100
+      value: 89.9
+    - type: recall_at_1000
+      value: 97.89999999999999
+    - type: recall_at_3
+      value: 67.4
+    - type: recall_at_5
+      value: 70.89999999999999
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MultilingualSentiment
+      type: C-MTEB/MultilingualSentiment-classification
+      config: default
+      split: validation
+      revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
+    metrics:
+    - type: accuracy
+      value: 76.87666666666667
+    - type: f1
+      value: 76.7317686219665
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB Ocnli
+      type: C-MTEB/OCNLI
+      config: default
+      split: validation
+      revision: 66e76a618a34d6d565d5538088562851e6daa7ec
+    metrics:
+    - type: cos_sim_accuracy
+      value: 79.64266377910124
+    - type: cos_sim_ap
+      value: 84.78274442344829
+    - type: cos_sim_f1
+      value: 81.16947472745292
+    - type: cos_sim_precision
+      value: 76.47058823529412
+    - type: cos_sim_recall
+      value: 86.48363252375924
+    - type: dot_accuracy
+      value: 79.64266377910124
+    - type: dot_ap
+      value: 84.7851404063692
+    - type: dot_f1
+      value: 81.16947472745292
+    - type: dot_precision
+      value: 76.47058823529412
+    - type: dot_recall
+      value: 86.48363252375924
+    - type: euclidean_accuracy
+      value: 79.64266377910124
+    - type: euclidean_ap
+      value: 84.78068373762378
+    - type: euclidean_f1
+      value: 81.14794656110837
+    - type: euclidean_precision
+      value: 76.35009310986965
+    - type: euclidean_recall
+      value: 86.58922914466737
+    - type: manhattan_accuracy
+      value: 79.48023822414727
+    - type: manhattan_ap
+      value: 84.72928897427576
+    - type: manhattan_f1
+      value: 81.32084770823064
+    - type: manhattan_precision
+      value: 76.24768946395564
+    - type: manhattan_recall
+      value: 87.11721224920802
+    - type: max_accuracy
+      value: 79.64266377910124
+    - type: max_ap
+      value: 84.7851404063692
+    - type: max_f1
+      value: 81.32084770823064
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB OnlineShopping
+      type: C-MTEB/OnlineShopping-classification
+      config: default
+      split: test
+      revision: e610f2ebd179a8fda30ae534c3878750a96db120
+    metrics:
+    - type: accuracy
+      value: 94.3
+    - type: ap
+      value: 92.8664032274438
+    - type: f1
+      value: 94.29311102997727
+  - task:
+      type: STS
+    dataset:
+      name: MTEB PAWSX
+      type: C-MTEB/PAWSX
+      config: default
+      split: test
+      revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
+    metrics:
+    - type: cos_sim_pearson
+      value: 48.51392279882909
+    - type: cos_sim_spearman
+      value: 54.06338895994974
+    - type: euclidean_pearson
+      value: 52.58480559573412
+    - type: euclidean_spearman
+      value: 54.06417276612201
+    - type: manhattan_pearson
+      value: 52.69525121721343
+    - type: manhattan_spearman
+      value: 54.048147455389675
+  - task:
+      type: STS
+    dataset:
+      name: MTEB QBQTC
+      type: C-MTEB/QBQTC
+      config: default
+      split: test
+      revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7
+    metrics:
+    - type: cos_sim_pearson
+      value: 29.728387290757325
+    - type: cos_sim_spearman
+      value: 31.366121633635284
+    - type: euclidean_pearson
+      value: 29.14588368552961
+    - type: euclidean_spearman
+      value: 31.36764411112844
+    - type: manhattan_pearson
+      value: 29.63517350523121
+    - type: manhattan_spearman
+      value: 31.94157020583762
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS22 (zh)
+      type: mteb/sts22-crosslingual-sts
+      config: zh
+      split: test
+      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
+    metrics:
+    - type: cos_sim_pearson
+      value: 63.64868296271406
+    - type: cos_sim_spearman
+      value: 66.12800618164744
+    - type: euclidean_pearson
+      value: 63.21405767340238
+    - type: euclidean_spearman
+      value: 66.12786567790748
+    - type: manhattan_pearson
+      value: 64.04300276525848
+    - type: manhattan_spearman
+      value: 66.5066857145652
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STSB
+      type: C-MTEB/STSB
+      config: default
+      split: test
+      revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.2302623912794
+    - type: cos_sim_spearman
+      value: 81.16833673266562
+    - type: euclidean_pearson
+      value: 79.47647843876024
+    - type: euclidean_spearman
+      value: 81.16944349524972
+    - type: manhattan_pearson
+      value: 79.84947238492208
+    - type: manhattan_spearman
+      value: 81.64626599410026
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB T2Reranking
+      type: C-MTEB/T2Reranking
+      config: default
+      split: dev
+      revision: 76631901a18387f85eaa53e5450019b87ad58ef9
+    metrics:
+    - type: map
+      value: 67.80129586475687
+    - type: mrr
+      value: 77.77402311635554
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB T2Retrieval
+      type: C-MTEB/T2Retrieval
+      config: default
+      split: dev
+      revision: 8731a845f1bf500a4f111cf1070785c793d10e64
+    metrics:
+    - type: map_at_1
+      value: 28.666999999999998
+    - type: map_at_10
+      value: 81.063
+    - type: map_at_100
+      value: 84.504
+    - type: map_at_1000
+      value: 84.552
+    - type: map_at_3
+      value: 56.897
+    - type: map_at_5
+      value: 70.073
+    - type: mrr_at_1
+      value: 92.087
+    - type: mrr_at_10
+      value: 94.132
+    - type: mrr_at_100
+      value: 94.19800000000001
+    - type: mrr_at_1000
+      value: 94.19999999999999
+    - type: mrr_at_3
+      value: 93.78999999999999
+    - type: mrr_at_5
+      value: 94.002
+    - type: ndcg_at_1
+      value: 92.087
+    - type: ndcg_at_10
+      value: 87.734
+    - type: ndcg_at_100
+      value: 90.736
+    - type: ndcg_at_1000
+      value: 91.184
+    - type: ndcg_at_3
+      value: 88.78
+    - type: ndcg_at_5
+      value: 87.676
+    - type: precision_at_1
+      value: 92.087
+    - type: precision_at_10
+      value: 43.46
+    - type: precision_at_100
+      value: 5.07
+    - type: precision_at_1000
+      value: 0.518
+    - type: precision_at_3
+      value: 77.49000000000001
+    - type: precision_at_5
+      value: 65.194
+    - type: recall_at_1
+      value: 28.666999999999998
+    - type: recall_at_10
+      value: 86.632
+    - type: recall_at_100
+      value: 96.646
+    - type: recall_at_1000
+      value: 98.917
+    - type: recall_at_3
+      value: 58.333999999999996
+    - type: recall_at_5
+      value: 72.974
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB TNews
+      type: C-MTEB/TNews-classification
+      config: default
+      split: validation
+      revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
+    metrics:
+    - type: accuracy
+      value: 52.971999999999994
+    - type: f1
+      value: 50.2898280984929
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB ThuNewsClusteringP2P
+      type: C-MTEB/ThuNewsClusteringP2P
+      config: default
+      split: test
+      revision: 5798586b105c0434e4f0fe5e767abe619442cf93
+    metrics:
+    - type: v_measure
+      value: 86.0797948663824
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB ThuNewsClusteringS2S
+      type: C-MTEB/ThuNewsClusteringS2S
+      config: default
+      split: test
+      revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
+    metrics:
+    - type: v_measure
+      value: 85.10759092255017
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB VideoRetrieval
+      type: C-MTEB/VideoRetrieval
+      config: default
+      split: dev
+      revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
+    metrics:
+    - type: map_at_1
+      value: 65.60000000000001
+    - type: map_at_10
+      value: 74.773
+    - type: map_at_100
+      value: 75.128
+    - type: map_at_1000
+      value: 75.136
+    - type: map_at_3
+      value: 73.05
+    - type: map_at_5
+      value: 74.13499999999999
+    - type: mrr_at_1
+      value: 65.60000000000001
+    - type: mrr_at_10
+      value: 74.773
+    - type: mrr_at_100
+      value: 75.128
+    - type: mrr_at_1000
+      value: 75.136
+    - type: mrr_at_3
+      value: 73.05
+    - type: mrr_at_5
+      value: 74.13499999999999
+    - type: ndcg_at_1
+      value: 65.60000000000001
+    - type: ndcg_at_10
+      value: 78.84299999999999
+    - type: ndcg_at_100
+      value: 80.40899999999999
+    - type: ndcg_at_1000
+      value: 80.57
+    - type: ndcg_at_3
+      value: 75.40599999999999
+    - type: ndcg_at_5
+      value: 77.351
+    - type: precision_at_1
+      value: 65.60000000000001
+    - type: precision_at_10
+      value: 9.139999999999999
+    - type: precision_at_100
+      value: 0.984
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 27.400000000000002
+    - type: precision_at_5
+      value: 17.380000000000003
+    - type: recall_at_1
+      value: 65.60000000000001
+    - type: recall_at_10
+      value: 91.4
+    - type: recall_at_100
+      value: 98.4
+    - type: recall_at_1000
+      value: 99.6
+    - type: recall_at_3
+      value: 82.19999999999999
+    - type: recall_at_5
+      value: 86.9
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB Waimai
+      type: C-MTEB/waimai-classification
+      config: default
+      split: test
+      revision: 339287def212450dcaa9df8c22bf93e9980c7023
+    metrics:
+    - type: accuracy
+      value: 89.47
+    - type: ap
+      value: 75.59561751845389
+    - type: f1
+      value: 87.95207751382563
+---
+# fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF
+This model was converted to GGUF format from [`Alibaba-NLP/gte-Qwen2-7B-instruct`](https://huggingface.co/Alibaba-NLP/gte-Qwen2-7B-instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
+Refer to the [original model card](https://huggingface.co/Alibaba-NLP/gte-Qwen2-7B-instruct) for more details on the model.
+## Use with llama.cpp
+Install llama.cpp through brew (works on Mac and Linux)
+```bash
+brew install llama.cpp
+```
+Invoke the llama.cpp server or the CLI.
+### CLI:
+```bash
+llama-cli --hf-repo fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF --hf-file gte-qwen2-7b-instruct-q8_0.gguf -p "The meaning to life and the universe is"
+```
+### Server:
+```bash
+llama-server --hf-repo fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF --hf-file gte-qwen2-7b-instruct-q8_0.gguf -c 2048
+```
+Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
+Step 1: Clone llama.cpp from GitHub.
+```
+git clone https://github.com/ggerganov/llama.cpp
+```
+Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
+```
+cd llama.cpp && LLAMA_CURL=1 make
+```
+Step 3: Run inference through the main binary.
+```
+./llama-cli --hf-repo fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF --hf-file gte-qwen2-7b-instruct-q8_0.gguf -p "The meaning to life and the universe is"
+```
+or
+```
+./llama-server --hf-repo fishbone64/gte-Qwen2-7B-instruct-Q8_0-GGUF --hf-file gte-qwen2-7b-instruct-q8_0.gguf -c 2048
+```