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SnehaPriyaaMP
/
Updated_final_data_model

PEFT
Safetensors
llama
4-bit precision
bitsandbytes
Model card Files Files and versions
xet
Community

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

  • Libraries
  • PEFT

    How to use SnehaPriyaaMP/Updated_final_data_model with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b-bnb-4bit")
    model = PeftModel.from_pretrained(base_model, "SnehaPriyaaMP/Updated_final_data_model")
  • Notebooks
  • Google Colab
  • Kaggle
Updated_final_data_model
5.93 GB
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  • 1 contributor
History: 5 commits
SnehaPriyaaMP's picture
SnehaPriyaaMP
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  • .gitattributes
    1.65 kB
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  • README.md
    5.1 kB
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  • SnehaPriyaaMP_WCAG_final_Combined_Datas - Complete dataset.csv
    49.4 MB
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  • adapter_config.json
    727 Bytes
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  • adapter_model.safetensors
    168 MB
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  • config.json
    1.16 kB
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  • generation_config.json
    198 Bytes
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  • model-00001-of-00002.safetensors
    4.65 GB
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  • model-00002-of-00002.safetensors
    1.05 GB
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  • model.safetensors.index.json
    132 kB
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  • special_tokens_map.json
    335 Bytes
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  • tokenizer.json
    9.09 MB
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  • tokenizer_config.json
    50.6 kB
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