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ashishkgpian
/
gemma_hf

Summarization
Transformers
Safetensors
gemma
text-generation
text-generation-inference
4-bit precision
bitsandbytes
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use ashishkgpian/gemma_hf 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="ashishkgpian/gemma_hf")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("ashishkgpian/gemma_hf")
    model = AutoModelForCausalLM.from_pretrained("ashishkgpian/gemma_hf")
  • Notebooks
  • Google Colab
  • Kaggle
gemma_hf
2.19 GB
Ctrl+K
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  • 1 contributor
History: 6 commits
ashishkgpian's picture
ashishkgpian
Upload tokenizer
761c3b9 verified about 2 years ago
  • .gitattributes
    1.57 kB
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  • README.md
    5.19 kB
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  • config.json
    1.15 kB
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  • generation_config.json
    137 Bytes
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  • model.safetensors
    2.16 GB
    xet
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  • special_tokens_map.json
    636 Bytes
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  • tokenizer.json
    17.5 MB
    xet
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  • tokenizer.model
    4.24 MB
    xet
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  • tokenizer_config.json
    2.16 kB
    Upload tokenizer about 2 years ago