Instructions to use google/gemma-4-31B-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/gemma-4-31B-it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="google/gemma-4-31B-it") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("google/gemma-4-31B-it") model = AutoModelForMultimodalLM.from_pretrained("google/gemma-4-31B-it") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- HuggingChat
- Notebooks
- Google Colab
- Kaggle
- AMD Developer Cloud
- Local Apps Settings
- vLLM
How to use google/gemma-4-31B-it with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "google/gemma-4-31B-it" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "google/gemma-4-31B-it", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/google/gemma-4-31B-it
- SGLang
How to use google/gemma-4-31B-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/gemma-4-31B-it" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "google/gemma-4-31B-it", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'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-4-31B-it" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "google/gemma-4-31B-it", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use google/gemma-4-31B-it with Docker Model Runner:
docker model run hf.co/google/gemma-4-31B-it
Love Gemma 4! A heartfelt plea from an independent developer regarding Antigravity CLI support
Dear Gemma Team,
I am writing this to express my deepest appreciation for your incredible work on Gemma 4. As an independent developer, Gemma 4 has quickly become my absolute favorite model for my daily workflows. Its remarkable balance of efficiency, intelligence, and accessibility has completely changed how I build and test ideas locally. Thank you for creating such a masterpiece!
However, I am writing to you today with a heavy heart regarding a roadblock that has recently broken my daily workflow.
Previously, I used Gemma 4 every single day in my terminal via the gemini-cli, authenticating seamlessly with my Google AI Studio API key. It was a perfect, friction-free environment for independent developers like me.
With the recent transition to the Antigravity CLI, the Google AI Studio API login entry has been removed, and Gemma 4 is no longer accessible within the new CLI roster. This sudden change has unexpectedly locked me—and many other individual creators—out of using your amazing model in our native terminal workflows.
I truly believe that the core vision of the Gemma family is to empower and serve a broader population, democraticizing AI for researchers, hobbyists, and independent developers who might not have enterprise-level cloud infrastructure.
Therefore, I humbly request the Gemma team to advocate on our behalf:
Bridge the Gap: Could you coordinate with the Antigravity CLI team to bring Gemma 4 back to the official model list?
Restore Access: Help us push for the re-introduction of the Google AI Studio API authentication entry in Antigravity, so individual developers can continue to innovate with your models.
Gemma 4 is too good a model to be left out of such an important developer tool. Please help us bring it back to the terminal so we can keep building with the technology we love.
Thank you so much for your time, your dedication, and for listening to the voice of a grateful developer.
Hi,
Thanks for the feedback!
as you noticed, unfortunately Gemma 4 is not supported in the Antigravity CLI. I'll ask the team if they could reconsider this for future versions.