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win2win
/
train-4-categories

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

Instructions to use win2win/train-4-categories with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use win2win/train-4-categories with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="win2win/train-4-categories")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("win2win/train-4-categories")
    model = AutoModel.from_pretrained("win2win/train-4-categories")
  • Notebooks
  • Google Colab
  • Kaggle
train-4-categories
266 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
win2win's picture
win2win
Upload tokenizer
9a8b9ea verified about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    5.17 kB
    Upload model about 1 year ago
  • config.json
    741 Bytes
    Upload model about 1 year ago
  • model.safetensors
    265 MB
    xet
    Upload model about 1 year ago
  • special_tokens_map.json
    695 Bytes
    Upload tokenizer about 1 year ago
  • tokenizer.json
    712 kB
    Upload tokenizer about 1 year ago
  • tokenizer_config.json
    1.41 kB
    Upload tokenizer about 1 year ago
  • vocab.txt
    232 kB
    Upload tokenizer about 1 year ago