Sentence Similarity
sentence-transformers
Safetensors
French
deberta-v2
passage-retrieval
Eval Results (legacy)
text-embeddings-inference
Instructions to use antoinelouis/biencoder-mdebertav3-mmarcoFR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use antoinelouis/biencoder-mdebertav3-mmarcoFR with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("antoinelouis/biencoder-mdebertav3-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
File size: 286 Bytes
cf46f6b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"bos_token": "[CLS]",
"cls_token": "[CLS]",
"eos_token": "[SEP]",
"mask_token": "[MASK]",
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"unk_token": {
"content": "[UNK]",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": false
}
}
|