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
      • Hardware
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

google
/
gemma-3-270m

Text Generation
Transformers
Safetensors
gemma3_text
gemma3
gemma
google
text-generation-inference
Model card Files Files and versions
xet
Community
33

Instructions to use google/gemma-3-270m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use google/gemma-3-270m with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="google/gemma-3-270m")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("google/gemma-3-270m")
    model = AutoModelForCausalLM.from_pretrained("google/gemma-3-270m", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • AMD Developer Cloud
  • Local Apps Settings
  • vLLM

    How to use google/gemma-3-270m with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "google/gemma-3-270m"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "google/gemma-3-270m",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/google/gemma-3-270m
  • SGLang

    How to use google/gemma-3-270m 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 "google/gemma-3-270m" \
        --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": "google/gemma-3-270m",
    		"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 "google/gemma-3-270m" \
            --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": "google/gemma-3-270m",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use google/gemma-3-270m with Docker Model Runner:

    docker model run hf.co/google/gemma-3-270m

Access Gemma on Hugging Face

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

To access Gemma on Hugging Face, you’re required to review and agree to Google’s usage license. To do this, please ensure you’re logged in to Hugging Face and click below. Requests are processed immediately.

Log in or Sign Up to review the conditions and access this model content.

Gated model
You can list files but not access them

Preview of files found in this repository
  • .gitattributes
    1.64 kB
    Upload IMG_20250816_162941143_HDR.jpg 12 months ago
  • IMG_20250816_162941143_HDR.jpg
    1.72 MB
    xet
    Upload IMG_20250816_162941143_HDR.jpg 12 months ago
  • README.md
    28.3 kB
    Update README.md 12 months ago
  • added_tokens.json
    35 Bytes
    uploading the PT weights for Gemma 3 270m about 1 year ago
  • config.json
    1.35 kB
    uploading the PT weights for Gemma 3 270m about 1 year ago
  • generation_config.json
    133 Bytes
    Removing chat template 12 months ago
  • model.safetensors
    536 MB
    xet
    uploading the PT weights for Gemma 3 270m about 1 year ago
  • special_tokens_map.json
    662 Bytes
    uploading the PT weights for Gemma 3 270m about 1 year ago
  • tokenizer.json
    33.4 MB
    xet
    uploading the PT weights for Gemma 3 270m about 1 year ago
  • tokenizer.model
    4.69 MB
    xet
    uploading the PT weights for Gemma 3 270m about 1 year ago
  • tokenizer_config.json
    1.16 MB
    uploading the PT weights for Gemma 3 270m about 1 year ago