Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
bert
mteb
Sentence Transformers
Eval Results (legacy)
Eval Results
text-embeddings-inference
Instructions to use intfloat/multilingual-e5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use intfloat/multilingual-e5-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("intfloat/multilingual-e5-small") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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change `model_max_length` value to fit positional embeddings number
053834d
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (538f7d96f9ba31b7c70f14578492fb49d3040a4e) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>7cf867c
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upload model weights
d2648e2 -
initial commit
a94d6a0