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mark-22
/
LoRA_dataclean_2

Text Generation
PEFT
Safetensors
English
qlora
lora
structured-output
json
no-cot
Model card Files Files and versions
xet
Community

Instructions to use mark-22/LoRA_dataclean_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use mark-22/LoRA_dataclean_2 with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit")
    model = PeftModel.from_pretrained(base_model, "mark-22/LoRA_dataclean_2")
  • Notebooks
  • Google Colab
  • Kaggle
LoRA_dataclean_2
543 MB
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  • 1 contributor
History: 7 commits
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mark-22
Update README.md
c88d3c4 verified 3 months ago
  • .gitattributes
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  • README.md
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  • adapter_config.json
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  • adapter_model.safetensors
    529 MB
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  • added_tokens.json
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  • special_tokens_map.json
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  • tokenizer.json
    11.4 MB
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  • tokenizer_config.json
    5.43 kB
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  • vocab.json
    2.78 MB
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