Sentence Similarity
sentence-transformers
ONNX
Safetensors
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use deepfile/multilingual-e5-small-onnx-qint8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use deepfile/multilingual-e5-small-onnx-qint8 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("deepfile/multilingual-e5-small-onnx-qint8") 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] - Notebooks
- Google Colab
- Kaggle
adding the default model
Browse files
README.md
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Optimization format: `ONNX`
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Quantization: `int8`
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Optimization format: `ONNX`
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Quantization: `int8`
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Original model is available at [intfloat/multilingual-e5-small](https://huggingface.co/intfloat/multilingual-e5-small)
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