Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

lenarc
/
llamalasa

Transformers
PyTorch
TensorBoard
Safetensors
English
Toki Pona
text-generation-inference
unsloth
llama
trl
Model card Files Files and versions
xet
Metrics Training metrics Community

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

  • Libraries
  • Transformers

    How to use lenarc/llamalasa with Transformers:

    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("lenarc/llamalasa", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • Unsloth Studio

    How to use lenarc/llamalasa 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 lenarc/llamalasa 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 lenarc/llamalasa to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for lenarc/llamalasa to start chatting
    Load model with FastModel
    pip install unsloth
    from unsloth import FastModel
    model, tokenizer = FastModel.from_pretrained(
        model_name="lenarc/llamalasa",
        max_seq_length=2048,
    )
llamalasa / runs
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
lenarc's picture
lenarc
Training in progress, step 12
2524252 verified over 1 year ago
  • Oct08_17-27-36_2785964ec193
    Training in progress, step 12 over 1 year ago
  • Oct08_17-55-16_2785964ec193
    Training in progress, step 12 over 1 year ago