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

chayuto
/
gemma-3n-e2b-it-solitaire-advisor-lora

Text Generation
MLX
English
mlx-lm
lora
gemma
gemma3n
klondike
solitaire
distillation
Model card Files Files and versions
xet
Community

Instructions to use chayuto/gemma-3n-e2b-it-solitaire-advisor-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • MLX

    How to use chayuto/gemma-3n-e2b-it-solitaire-advisor-lora with MLX:

    # Make sure mlx-lm is installed
    # pip install --upgrade mlx-lm
    # if on a CUDA device, also pip install mlx[cuda]
    
    # Generate text with mlx-lm
    from mlx_lm import load, generate
    
    model, tokenizer = load("chayuto/gemma-3n-e2b-it-solitaire-advisor-lora")
    
    prompt = "Once upon a time in"
    text = generate(model, tokenizer, prompt=prompt, verbose=True)
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • LM Studio
  • MLX LM

    How to use chayuto/gemma-3n-e2b-it-solitaire-advisor-lora with MLX LM:

    Generate or start a chat session
    # Install MLX LM
    uv tool install mlx-lm
    # Generate some text
    mlx_lm.generate --model "chayuto/gemma-3n-e2b-it-solitaire-advisor-lora" --prompt "Once upon a time"
gemma-3n-e2b-it-solitaire-advisor-lora
226 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
chayuto's picture
chayuto
Link to Gemma 4 E2B successor; clean doc characters
dca55b9 verified 20 days ago
  • checkpoints
    v1: 1000-iter LoRA on Gemma 3n E2B (halves teacher tier gap, eliminates illegal moves) about 1 month ago
  • eval
    v1.1: promote iter-750 as canonical (best of 4 checkpoints by tier+foundation), add learning curve, fix draw-1 wording, beef up Usage with concrete example, plain-text typography pass about 1 month ago
  • training
    v1.1: promote iter-750 as canonical (best of 4 checkpoints by tier+foundation), add learning curve, fix draw-1 wording, beef up Usage with concrete example, plain-text typography pass about 1 month ago
  • .gitattributes
    1.52 kB
    initial commit about 1 month ago
  • README.md
    24.3 kB
    Link to Gemma 4 E2B successor; clean doc characters 20 days ago
  • adapter_config.json
    1.22 kB
    v1: 1000-iter LoRA on Gemma 3n E2B (halves teacher tier gap, eliminates illegal moves) about 1 month ago
  • adapters.safetensors
    45.1 MB
    xet
    v1.1: promote iter-750 as canonical (best of 4 checkpoints by tier+foundation), add learning curve, fix draw-1 wording, beef up Usage with concrete example, plain-text typography pass about 1 month ago