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trishpurkait
/
billstructai-qwen-lora

Text Generation
PEFT
Safetensors
lora
qlora
invoice-extraction
information-extraction
qwen2.5
ocr
conversational
Model card Files Files and versions
xet
Community

Instructions to use trishpurkait/billstructai-qwen-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use trishpurkait/billstructai-qwen-lora with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct")
    model = PeftModel.from_pretrained(base_model, "trishpurkait/billstructai-qwen-lora")
  • Notebooks
  • Google Colab
  • Kaggle
billstructai-qwen-lora
123 MB
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  • 1 contributor
History: 2 commits
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trishpurkait
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  • .gitattributes
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  • README.md
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  • adapter_config.json
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  • adapter_model.safetensors
    73.9 MB
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  • chat_template.jinja
    2.51 kB
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  • optimizer.pt
    38 MB
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  • rng_state.pth
    14.6 kB
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  • scaler.pt

    Pickle imports

    • No problematic imports detected

    What is a pickle import?

    1.38 kB
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  • scheduler.pt
    1.47 kB
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  • tokenizer.json
    11.4 MB
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  • tokenizer_config.json
    665 Bytes
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  • trainer_state.json
    19.6 kB
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  • training_args.bin
    5.2 kB
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