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npnik4
/
resume-summarizer

Summarization
Transformers
PyTorch
English
llama
text-generation
text-generation-inference
Model card Files Files and versions
xet
Community

Instructions to use npnik4/resume-summarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use npnik4/resume-summarizer with Transformers:

    # Use a pipeline as a high-level helper
    # Warning: Pipeline type "summarization" is no longer supported in transformers v5.
    # You must load the model directly (see below) or downgrade to v4.x with:
    # 'pip install "transformers<5.0.0'
    from transformers import pipeline
    
    pipe = pipeline("summarization", model="npnik4/resume-summarizer")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("npnik4/resume-summarizer")
    model = AutoModelForCausalLM.from_pretrained("npnik4/resume-summarizer")
  • Notebooks
  • Google Colab
  • Kaggle
resume-summarizer
137 MB
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  • 1 contributor
History: 13 commits
npnik4's picture
npnik4
Update README.md
d90b7d5 verified about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
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  • adapter_config.json
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  • adapter_model.bin

    Detected Pickle imports (3)

    • "torch._utils._rebuild_tensor_v2",
    • "collections.OrderedDict",
    • "torch.FloatStorage"

    What is a pickle import?

    134 MB
    xet
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  • added_tokens.json
    21 Bytes
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  • config.json
    582 Bytes
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  • pytorch_model.bin.index.json
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  • special_tokens_map.json
    434 Bytes
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  • tokenizer.json
    1.84 MB
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  • tokenizer.model
    500 kB
    xet
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  • tokenizer_config.json
    695 Bytes
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