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VSSA-SDSA
/
LT_QA_demo

Text Generation
PEFT
Safetensors
Lithuanian
unsloth
lithuanian
question-answering
conversational
instruction-tuned
lora
Model card Files Files and versions
xet
Community

Instructions to use VSSA-SDSA/LT_QA_demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use VSSA-SDSA/LT_QA_demo with PEFT:

    Task type is invalid.
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • Unsloth Studio new

    How to use VSSA-SDSA/LT_QA_demo 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 VSSA-SDSA/LT_QA_demo 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 VSSA-SDSA/LT_QA_demo to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for VSSA-SDSA/LT_QA_demo to start chatting
    Load model with FastModel
    pip install unsloth
    from unsloth import FastModel
    model, tokenizer = FastModel.from_pretrained(
        model_name="VSSA-SDSA/LT_QA_demo",
        max_seq_length=2048,
    )
LT_QA_demo
557 MB
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  • 2 contributors
History: 5 commits
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DariusAm
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