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nickprock
/
multi-sentence-BERTino

Sentence Similarity
sentence-transformers
ONNX
Safetensors
Italian
distilbert
feature-extraction
dense
matryoshka
information-retrieval
Generated from Trainer
text-embeddings-inference
Model card Files Files and versions
xet
Community
5

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]
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
multi-sentence-BERTino
339 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 18 commits
nickprock's picture
nickprock
Update README.md
f3a0601 verified about 2 months ago
  • 1_Pooling
    Upgrade to V2 via Multi-Task Learning about 2 months ago
  • onnx
    Add exported onnx model 'model_qint8_avx512_vnni.onnx' (#1) about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    8.01 kB
    Update README.md about 2 months ago
  • config.json
    631 Bytes
    Upgrade to V2 via Multi-Task Learning about 2 months ago
  • config_sentence_transformers.json
    301 Bytes
    Upgrade to V2 via Multi-Task Learning about 2 months ago
  • model.safetensors
    270 MB
    xet
    Upgrade to V5: Matryoshka Loss with Asymmetric Weights [1.0, 0.4, 0.2, 0.2]. Minimized truncation tax at 768d. about 2 months ago
  • modules.json
    242 Bytes
    Upgrade to V2 via Multi-Task Learning about 2 months ago
  • sentence_bert_config.json
    60 Bytes
    Upgrade to V2 via Multi-Task Learning about 2 months ago
  • special_tokens_map.json
    125 Bytes
    Upload 11 files over 2 years ago
  • tokenizer.json
    732 kB
    Upload 11 files over 2 years ago
  • tokenizer_config.json
    683 Bytes
    Upgrade to V5: Matryoshka Loss with Asymmetric Weights [1.0, 0.4, 0.2, 0.2]. Minimized truncation tax at 768d. about 2 months ago
  • vocab.txt
    243 kB
    Upload 11 files over 2 years ago