Sentence Similarity
sentence-transformers
TensorBoard
Safetensors
xlm-roberta
feature-extraction
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use manu/bge-fr-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use manu/bge-fr-en with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("manu/bge-fr-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
Download training_args.bin from manu/bge-fr-en: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/manu/bge-fr-en/resolve/main/training_args.bin
- Command line
-
hf download hf://manu/bge-fr-en/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/manu/bge-fr-en/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- 3eb29206aaf77975a3923c6cd256e2ac696fa4abb52c12af2f7e996e0b79e4c7
- Size of remote file:
- 5.18 kB
- SHA256:
- b7d9ce1dff67f7459efd7e0c3c31ea127bb2c9e0a449593e8411f88c85ffd8ce
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