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svjack
/
setfit_info_cls

Feature Extraction
Transformers
Safetensors
bert
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use svjack/setfit_info_cls with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use svjack/setfit_info_cls with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="svjack/setfit_info_cls")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("svjack/setfit_info_cls")
    model = AutoModel.from_pretrained("svjack/setfit_info_cls")
  • Notebooks
  • Google Colab
  • Kaggle
setfit_info_cls
96.4 MB
Ctrl+K
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  • 1 contributor
History: 3 commits
svjack's picture
svjack
Delete README.md
5fe379f verified about 2 years ago
  • 1_Pooling
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  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • config.json
    737 Bytes
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  • config_sentence_transformers.json
    172 Bytes
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  • config_setfit.json
    53 Bytes
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  • model.safetensors
    95.8 MB
    xet
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  • model_head.pkl
    4.94 kB
    xet
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  • modules.json
    349 Bytes
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  • sentence_bert_config.json
    52 Bytes
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  • special_tokens_map.json
    695 Bytes
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  • tokenizer.json
    439 kB
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  • tokenizer_config.json
    1.43 kB
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  • vocab.txt
    110 kB
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