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dlyog
/
gemma-cure

Text Generation
PEFT
Safetensors
English
drug-discovery
chemistry
smiles
lora
unsloth
gemma4
biology
fine-tuned
healthcare
conversational
Model card Files Files and versions
xet
Community

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

  • Libraries
  • PEFT

    How to use dlyog/gemma-cure with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-4-E2B-it-unsloth-bnb-4bit")
    model = PeftModel.from_pretrained(base_model, "dlyog/gemma-cure")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • Unsloth Desktop
gemma-cure
281 MB
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  • 1 contributor
History: 3 commits
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tarunchy
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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
    248 MB
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  • chat_template.jinja
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  • processor_config.json
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  • tokenizer.json
    32.2 MB
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  • tokenizer_config.json
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