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

Monibee-Fudgekins
/
gemma-coder-dev

Text Generation
Transformers
Safetensors
code
coding-assistant
qlora
unsloth
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use Monibee-Fudgekins/gemma-coder-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Monibee-Fudgekins/gemma-coder-dev with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="Monibee-Fudgekins/gemma-coder-dev")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("Monibee-Fudgekins/gemma-coder-dev", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use Monibee-Fudgekins/gemma-coder-dev with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "Monibee-Fudgekins/gemma-coder-dev"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Monibee-Fudgekins/gemma-coder-dev",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/Monibee-Fudgekins/gemma-coder-dev
  • SGLang

    How to use Monibee-Fudgekins/gemma-coder-dev with SGLang:

    Install from pip and serve model
    # Install SGLang from pip:
    pip install sglang
    # Start the SGLang server:
    python3 -m sglang.launch_server \
        --model-path "Monibee-Fudgekins/gemma-coder-dev" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Monibee-Fudgekins/gemma-coder-dev",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker images
    docker run --gpus all \
        --shm-size 32g \
        -p 30000:30000 \
        -v ~/.cache/huggingface:/root/.cache/huggingface \
        --env "HF_TOKEN=<secret>" \
        --ipc=host \
        lmsysorg/sglang:latest \
        python3 -m sglang.launch_server \
            --model-path "Monibee-Fudgekins/gemma-coder-dev" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Monibee-Fudgekins/gemma-coder-dev",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Unsloth Studio

    How to use Monibee-Fudgekins/gemma-coder-dev 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 Monibee-Fudgekins/gemma-coder-dev 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 Monibee-Fudgekins/gemma-coder-dev to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for Monibee-Fudgekins/gemma-coder-dev to start chatting
    Load model with FastModel
    pip install unsloth
    from unsloth import FastModel
    model, tokenizer = FastModel.from_pretrained(
        model_name="Monibee-Fudgekins/gemma-coder-dev",
        max_seq_length=2048,
    )
  • Docker Model Runner

    How to use Monibee-Fudgekins/gemma-coder-dev with Docker Model Runner:

    docker model run hf.co/Monibee-Fudgekins/gemma-coder-dev
gemma-coder-dev
975 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 20 commits
Monibee-Fudgekins's picture
Monibee-Fudgekins
progress: cycle 1 999/4000 (next ds idx 2)
537b55d verified 2 days ago
  • .gitattributes
    1.52 kB
    initial commit 10 days ago
  • README.md
    3.3 kB
    Upload model trained with Unsloth 2 days ago
  • adapter_config.json
    1.46 kB
    Upload model trained with Unsloth 3 days ago
  • adapter_model.safetensors
    975 MB
    xet
    Upload model trained with Unsloth 2 days ago
  • progress.json
    67 Bytes
    progress: cycle 1 999/4000 (next ds idx 2) 2 days ago