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
| { | |
| "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]" | |
| } | |