Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
xlm-roberta
mteb
Sentence Transformers
Eval Results (legacy)
Eval Results
text-embeddings-inference
Instructions to use intfloat/multilingual-e5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use intfloat/multilingual-e5-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("intfloat/multilingual-e5-base") 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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Adding ONNX file of this model
Beep boop I am the [ONNX export bot 🤖🏎️](https://huggingface.co/spaces/onnx/export). On behalf of [romaindeveaud](https://huggingface.co/romaindeveaud), I would like to add to this repository the model converted to ONNX. What is ONNX? It stands for "Open Neural Network Exchange", and is the most commonly used open standard for machine learning interoperability. You can find out more at [onnx.ai](https://onnx.ai/)! The exported ONNX model can be then be consumed by various backends as TensorRT or TVM, or simply be used in a few lines with 🤗 Optimum through ONNX Runtime, check out how [here](https://huggingface.co/docs/optimum/main/en/onnxruntime/usage_guides/models)!7d87603
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add sentence similarity tag
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track tokenizer.json with lfs
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Adding `safetensors` variant of this model (#6)
- Adding `safetensors` variant of this model (5c31b33181f6c6bfbbce758a5900f9407bbcff42) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>a1c23e4
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sentence transformers (#5)
- sbert (73faffbff62768f15b166b0b6866e99b993f6be4)830e3a9
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upload model weights
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initial commit
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