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Vjay15
/
LLaMA_3_8B_Science_LoRA

Safetensors
unsloth
Model card Files Files and versions
xet
Community

Instructions to use Vjay15/LLaMA_3_8B_Science_LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Local Apps
  • Unsloth Studio new

    How to use Vjay15/LLaMA_3_8B_Science_LoRA with Unsloth Studio:

    Install Unsloth Studio (macOS, Linux, WSL)
    curl -fsSL https://unsloth.ai/install.sh | sh
    # Run unsloth studio
    unsloth studio -H 0.0.0.0 -p 8888
    # Then open http://localhost:8888 in your browser
    # Search for Vjay15/LLaMA_3_8B_Science_LoRA to start chatting
    Install Unsloth Studio (Windows)
    irm https://unsloth.ai/install.ps1 | iex
    # Run unsloth studio
    unsloth studio -H 0.0.0.0 -p 8888
    # Then open http://localhost:8888 in your browser
    # Search for Vjay15/LLaMA_3_8B_Science_LoRA to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for Vjay15/LLaMA_3_8B_Science_LoRA to start chatting
    Load model with FastModel
    pip install unsloth
    from unsloth import FastModel
    model, tokenizer = FastModel.from_pretrained(
        model_name="Vjay15/LLaMA_3_8B_Science_LoRA",
        max_seq_length=2048,
    )
LLaMA_3_8B_Science_LoRA
185 MB
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  • 1 contributor
History: 3 commits
Vjay15's picture
Vjay15
Upload model trained with Unsloth
fd4c3f3 verified 10 months ago
  • .gitattributes
    1.57 kB
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  • README.md
    42 Bytes
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  • adapter_config.json
    916 Bytes
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  • adapter_model.safetensors
    168 MB
    xet
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  • chat_template.jinja
    389 Bytes
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  • special_tokens_map.json
    459 Bytes
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  • tokenizer.json
    17.2 MB
    xet
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  • tokenizer_config.json
    50.6 kB
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