Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use intfloat/e5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use intfloat/e5-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("intfloat/e5-small") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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- type: cos_sim_pearson
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value: 31.523347880124497
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- type: cos_sim_spearman
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value: 31.
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value: 24.
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value: 23.
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type: Retrieval
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dataset:
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value: 78.26696165191743
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language:
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- en
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---
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# E5-small
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- type: cos_sim_pearson
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value: 31.523347880124497
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- type: cos_sim_spearman
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value: 31.388214436391014
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- type: dot_pearson
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value: 24.55403435439901
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- type: dot_spearman
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value: 23.50153210841191
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- task:
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type: Retrieval
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dataset:
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value: 78.26696165191743
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language:
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- en
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license: mit
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---
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# E5-small
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