Instructions to use google/functiongemma-270m-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/functiongemma-270m-it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="google/functiongemma-270m-it")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("google/functiongemma-270m-it", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use google/functiongemma-270m-it with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "google/functiongemma-270m-it" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "google/functiongemma-270m-it", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/google/functiongemma-270m-it
- SGLang
How to use google/functiongemma-270m-it 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/functiongemma-270m-it" \ --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/functiongemma-270m-it", "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/functiongemma-270m-it" \ --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/functiongemma-270m-it", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use google/functiongemma-270m-it with Docker Model Runner:
docker model run hf.co/google/functiongemma-270m-it
Request: DOI
I need this 😩
Hi @maalikishaak
Welcome to Google's Gemma models, thanks for reaching out . The Gemma models are Gated models, which means you need to request access directly from the model's model card section on Hugging Face and use a valid access token to load the model locally.
You can access the google/functiongemma-270m-it model using the granted access token or download the model weights for local use. For generating access token in HuggingFace, could you please refer this documentation: https://huggingface.co/docs/transformers.js/en/guides/private
Thanks