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mtzig
/
tinyllama_run

Token Classification
Transformers
Safetensors
llama
Generated from Trainer
text-generation-inference
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use mtzig/tinyllama_run with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="mtzig/tinyllama_run")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("mtzig/tinyllama_run")
    model = AutoModelForTokenClassification.from_pretrained("mtzig/tinyllama_run", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
tinyllama_run
540 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
mtzig's picture
mtzig
Model save
9239049 verified almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    1.24 kB
    Model save almost 2 years ago
  • config.json
    730 Bytes
    Model save almost 2 years ago
  • model.safetensors
    535 MB
    xet
    Model save almost 2 years ago
  • special_tokens_map.json
    437 Bytes
    Model save almost 2 years ago
  • tokenizer.json
    3.62 MB
    Model save almost 2 years ago
  • tokenizer.model
    500 kB
    xet
    Model save almost 2 years ago
  • tokenizer_config.json
    947 Bytes
    Model save almost 2 years ago
  • training_args.bin
    5.18 kB
    xet
    Model save almost 2 years ago