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windmaple
/
gemma-chinese

PEFT
TensorBoard
Safetensors
gemma
trl
sft
Generated from Trainer
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use windmaple/gemma-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use windmaple/gemma-chinese with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2b")
    model = PeftModel.from_pretrained(base_model, "windmaple/gemma-chinese")
  • Notebooks
  • Google Colab
  • Kaggle
gemma-chinese
10.5 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 27 commits
windmaple's picture
windmaple
Training in progress, epoch 1
9bb0736 verified over 2 years ago
  • runs
    Training in progress, epoch 1 over 2 years ago
  • .gitattributes
    1.57 kB
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  • README.md
    1.21 kB
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  • adapter_config.json
    670 Bytes
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  • adapter_model.safetensors
    5.45 GB
    xet
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  • added_tokens.json
    53 Bytes
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  • config.json
    659 Bytes
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  • generation_config.json
    132 Bytes
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  • model-00001-of-00003.safetensors
    1.95 GB
    xet
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  • model-00002-of-00003.safetensors
    1.98 GB
    xet
    Training in progress, epoch 1 over 2 years ago
  • model-00003-of-00003.safetensors
    1.08 GB
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  • model.safetensors.index.json
    13.5 kB
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  • special_tokens_map.json
    557 Bytes
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  • tokenizer.json
    17.5 MB
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  • tokenizer.model
    4.24 MB
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  • tokenizer_config.json
    1.78 kB
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  • training_args.bin
    4.92 kB
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