Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
ONNX
Safetensors
OpenVINO
Transformers
distilbert
feature-extraction
text-embeddings-inference
Instructions to use sentence-transformers/distilbert-multilingual-nli-stsb-quora-ranking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sentence-transformers/distilbert-multilingual-nli-stsb-quora-ranking with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/distilbert-multilingual-nli-stsb-quora-ranking") 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 sentence-transformers/distilbert-multilingual-nli-stsb-quora-ranking with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sentence-transformers/distilbert-multilingual-nli-stsb-quora-ranking") model = AutoModel.from_pretrained("sentence-transformers/distilbert-multilingual-nli-stsb-quora-ranking") - Inference
- Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,37 +1,11 @@
|
|
| 1 |
---
|
| 2 |
pipeline_tag: sentence-similarity
|
|
|
|
| 3 |
tags:
|
| 4 |
- sentence-transformers
|
| 5 |
- feature-extraction
|
| 6 |
- sentence-similarity
|
| 7 |
- transformers
|
| 8 |
-
- transformers
|
| 9 |
-
- transformers
|
| 10 |
-
- transformers
|
| 11 |
-
- transformers
|
| 12 |
-
- transformers
|
| 13 |
-
- transformers
|
| 14 |
-
- transformers
|
| 15 |
-
- transformers
|
| 16 |
-
- transformers
|
| 17 |
-
- transformers
|
| 18 |
-
- transformers
|
| 19 |
-
- transformers
|
| 20 |
-
- transformers
|
| 21 |
-
- transformers
|
| 22 |
-
- transformers
|
| 23 |
-
- transformers
|
| 24 |
-
- transformers
|
| 25 |
-
- transformers
|
| 26 |
-
- transformers
|
| 27 |
-
- transformers
|
| 28 |
-
- transformers
|
| 29 |
-
- transformers
|
| 30 |
-
- transformers
|
| 31 |
-
- transformers
|
| 32 |
-
- transformers
|
| 33 |
-
- transformers
|
| 34 |
-
- transformers
|
| 35 |
---
|
| 36 |
|
| 37 |
# sentence-transformers/distilbert-multilingual-nli-stsb-quora-ranking
|
|
|
|
| 1 |
---
|
| 2 |
pipeline_tag: sentence-similarity
|
| 3 |
+
license: apache-2.0
|
| 4 |
tags:
|
| 5 |
- sentence-transformers
|
| 6 |
- feature-extraction
|
| 7 |
- sentence-similarity
|
| 8 |
- transformers
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 9 |
---
|
| 10 |
|
| 11 |
# sentence-transformers/distilbert-multilingual-nli-stsb-quora-ranking
|