Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
English
bert
mteb
sentence transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use vectoriseai/bge-small-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use vectoriseai/bge-small-en with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("vectoriseai/bge-small-en") 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] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c42ae94c7598447fc4c8961d1cb092c74143149750638e3b4107bb8bcf41c68
- Size of remote file:
- 134 MB
- SHA256:
- 662afbeea6d658f743f3fc11b0e710a0a092837b220eaa7ca0bde604df562153
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