Sentence Similarity
sentence-transformers
ONNX
Safetensors
Italian
distilbert
feature-extraction
dense
matryoshka
information-retrieval
Generated from Trainer
text-embeddings-inference
Instructions to use nickprock/multi-sentence-BERTino with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nickprock/multi-sentence-BERTino with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nickprock/multi-sentence-BERTino") sentences = [ "Ci stiamo muovendo \"... rispetto al commovente telaio cosmico di riposo ... a circa 371 km/s verso la costellazione del Leone\".", "Una donna sta tagliando le cipolle verdi.", "Non c'è un 'fermo' che non sia relativo a qualche altro oggetto.", "Un gruppo di anziani si mette in posa attorno a un tavolo da pranzo." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| { | |
| "backend": "tokenizers", | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "[CLS]", | |
| "do_basic_tokenize": true, | |
| "do_lower_case": true, | |
| "full_tokenizer_file": null, | |
| "is_local": true, | |
| "mask_token": "[MASK]", | |
| "max_len": 512, | |
| "max_length": 512, | |
| "model_max_length": 512, | |
| "never_split": null, | |
| "pad_to_multiple_of": null, | |
| "pad_token": "[PAD]", | |
| "pad_token_type_id": 0, | |
| "padding_side": "right", | |
| "sep_token": "[SEP]", | |
| "stride": 0, | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "TokenizersBackend", | |
| "truncation_side": "right", | |
| "truncation_strategy": "longest_first", | |
| "unk_token": "[UNK]" | |
| } | |