Sentence Similarity
sentence-transformers
PyTorch
Safetensors
French
xlm-roberta
passage-retrieval
Eval Results (legacy)
text-embeddings-inference
Instructions to use antoinelouis/biencoder-mMiniLMv2-L6-mmarcoFR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use antoinelouis/biencoder-mMiniLMv2-L6-mmarcoFR with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("antoinelouis/biencoder-mMiniLMv2-L6-mmarcoFR") sentences = [ "C'est une personne heureuse", "C'est un chien heureux", "C'est une personne très heureuse", "Aujourd'hui est une journée ensoleillée" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe584e09808b408472e9556eb0d8db4b797690702ab6f43ad18e59f5b5b2cd10
- Size of remote file:
- 17.1 MB
- SHA256:
- b60b6b43406a48bf3638526314f3d232d97058bc93472ff2de930d43686fa441
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.