Sentence Similarity
sentence-transformers
PyTorch
Safetensors
French
electra
passage-retrieval
Eval Results (legacy)
Instructions to use antoinelouis/biencoder-electra-base-mmarcoFR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use antoinelouis/biencoder-electra-base-mmarcoFR with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("antoinelouis/biencoder-electra-base-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: 460 Bytes
b8fcf2a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"cls_token": "[CLS]",
"do_basic_tokenize": true,
"do_lower_case": false,
"mask_token": "[MASK]",
"max_len": 512,
"model_max_length": 128,
"name_or_path": "dbmdz/electra-base-french-europeana-cased-discriminator",
"never_split": null,
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"special_tokens_map_file": null,
"strip_accents": null,
"tokenize_chinese_chars": true,
"tokenizer_class": "ElectraTokenizer",
"unk_token": "[UNK]"
}
|