Instructions to use recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp")
model = AutoModelForCausalLM.from_pretrained("recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp

SGLang

How to use recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp with Docker Model Runner:
```
docker model run hf.co/recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
```

recoilme

leaderboard-pt-pr-bot commited on Jan 15, 2025

Commit

8955cd3

verified ·

1 Parent(s): 5a4f729

Adding the Open Portuguese LLM Leaderboard Evaluation Results (#3)

Browse files

- Adding the Open Portuguese LLM Leaderboard Evaluation Results (1bad910bd8961156f57b5bb207f613c88a23eae4)

Co-authored-by: Open PT LLM Leaderboard PR Bot <leaderboard-pt-pr-bot@users.noreply.huggingface.co>

Files changed (1) hide show

README.md +170 -13

README.md CHANGED Viewed

@@ -17,8 +17,7 @@ model-index:
       value: 76.49
       name: strict accuracy
     source:
-      url: >-
-        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -33,8 +32,7 @@ model-index:
       value: 42.25
       name: normalized accuracy
     source:
-      url: >-
-        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -49,8 +47,7 @@ model-index:
       value: 1.74
       name: exact match
     source:
-      url: >-
-        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -65,8 +62,7 @@ model-index:
       value: 10.74
       name: acc_norm
     source:
-      url: >-
-        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -81,8 +77,7 @@ model-index:
       value: 12.39
       name: acc_norm
     source:
-      url: >-
-        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -99,9 +94,152 @@ model-index:
       value: 35.63
       name: accuracy
     source:
-      url: >-
-        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
       name: Open LLM Leaderboard
 ---
 # Gemma-2-Ataraxy-Gemmasutra-9B-slerp
@@ -142,4 +280,23 @@ Detailed results can be found [here](https://huggingface.co/datasets/open-llm-le
 |MATH Lvl 5 (4-Shot)| 1.74|
 |GPQA (0-shot)      |10.74|
 |MuSR (0-shot)      |12.39|
-|MMLU-PRO (5-shot)  |35.63|

       value: 76.49
       name: strict accuracy
     source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
       name: Open LLM Leaderboard
   - task:
       type: text-generation
       value: 42.25
       name: normalized accuracy
     source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
       name: Open LLM Leaderboard
   - task:
       type: text-generation
       value: 1.74
       name: exact match
     source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
       name: Open LLM Leaderboard
   - task:
       type: text-generation
       value: 10.74
       name: acc_norm
     source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
       name: Open LLM Leaderboard
   - task:
       type: text-generation
       value: 12.39
       name: acc_norm
     source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
       name: Open LLM Leaderboard
   - task:
       type: text-generation
       value: 35.63
       name: accuracy
     source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
       name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: ENEM Challenge (No Images)
+      type: eduagarcia/enem_challenge
+      split: train
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc
+      value: 75.65
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
+      name: Open Portuguese LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: BLUEX (No Images)
+      type: eduagarcia-temp/BLUEX_without_images
+      split: train
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc
+      value: 64.26
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
+      name: Open Portuguese LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: OAB Exams
+      type: eduagarcia/oab_exams
+      split: train
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc
+      value: 53.76
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
+      name: Open Portuguese LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Assin2 RTE
+      type: assin2
+      split: test
+      args:
+        num_few_shot: 15
+    metrics:
+    - type: f1_macro
+      value: 93.21
+      name: f1-macro
+    source:
+      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
+      name: Open Portuguese LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Assin2 STS
+      type: eduagarcia/portuguese_benchmark
+      split: test
+      args:
+        num_few_shot: 15
+    metrics:
+    - type: pearson
+      value: 80.91
+      name: pearson
+    source:
+      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
+      name: Open Portuguese LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: FaQuAD NLI
+      type: ruanchaves/faquad-nli
+      split: test
+      args:
+        num_few_shot: 15
+    metrics:
+    - type: f1_macro
+      value: 77.39
+      name: f1-macro
+    source:
+      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
+      name: Open Portuguese LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: HateBR Binary
+      type: ruanchaves/hatebr
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: f1_macro
+      value: 87.61
+      name: f1-macro
+    source:
+      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
+      name: Open Portuguese LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: PT Hate Speech Binary
+      type: hate_speech_portuguese
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: f1_macro
+      value: 66.84
+      name: f1-macro
+    source:
+      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
+      name: Open Portuguese LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: tweetSentBR
+      type: eduagarcia/tweetsentbr_fewshot
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: f1_macro
+      value: 66.14
+      name: f1-macro
+    source:
+      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
+      name: Open Portuguese LLM Leaderboard
 ---
 # Gemma-2-Ataraxy-Gemmasutra-9B-slerp
 |MATH Lvl 5 (4-Shot)| 1.74|
 |GPQA (0-shot)      |10.74|
 |MuSR (0-shot)      |12.39|
+|MMLU-PRO (5-shot)  |35.63|
+# Open Portuguese LLM Leaderboard Evaluation Results
+Detailed results can be found [here](https://huggingface.co/datasets/eduagarcia-temp/llm_pt_leaderboard_raw_results/tree/main/recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp) and on the [🚀 Open Portuguese LLM Leaderboard](https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard)
+|          Metric          |  Value  |
+|--------------------------|---------|
+|Average                   |**73.97**|
+|ENEM Challenge (No Images)|    75.65|
+|BLUEX (No Images)         |    64.26|
+|OAB Exams                 |    53.76|
+|Assin2 RTE                |    93.21|
+|Assin2 STS                |    80.91|
+|FaQuAD NLI                |    77.39|
+|HateBR Binary             |    87.61|
+|PT Hate Speech Binary     |    66.84|
+|tweetSentBR               |    66.14|