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tmp-org
/
netto_v1

Text Classification
setfit
Safetensors
sentence-transformers
new
generated_from_setfit_trainer
custom_code
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use tmp-org/netto_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • setfit

    How to use tmp-org/netto_v1 with setfit:

    from setfit import SetFitModel
    
    model = SetFitModel.from_pretrained("tmp-org/netto_v1")
  • sentence-transformers

    How to use tmp-org/netto_v1 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("tmp-org/netto_v1", trust_remote_code=True)
    
    sentences = [
        "The weather is lovely today.",
        "It's so sunny outside!",
        "He drove to the stadium."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [3, 3]
  • Notebooks
  • Google Colab
  • Kaggle
netto_v1
1.24 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
SzymonKozl's picture
SzymonKozl
Push model using huggingface_hub.
6e2d142 verified 2 months ago
  • 1_Pooling
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  • .gitattributes
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  • README.md
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  • config.json
    1.47 kB
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  • config_sentence_transformers.json
    284 Bytes
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  • config_setfit.json
    793 Bytes
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  • configuration.py
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  • model.safetensors
    1.22 GB
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  • model_head.pkl
    170 kB
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  • modeling.py
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  • modules.json
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  • sentence_bert_config.json
    58 Bytes
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  • special_tokens_map.json
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  • tokenizer.json
    17.1 MB
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  • tokenizer_config.json
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