Instructions to use google/vaultgemma-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/vaultgemma-1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="google/vaultgemma-1b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("google/vaultgemma-1b") model = AutoModelForCausalLM.from_pretrained("google/vaultgemma-1b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use google/vaultgemma-1b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "google/vaultgemma-1b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "google/vaultgemma-1b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/google/vaultgemma-1b
- SGLang
How to use google/vaultgemma-1b 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/vaultgemma-1b" \ --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/vaultgemma-1b", "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/vaultgemma-1b" \ --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/vaultgemma-1b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use google/vaultgemma-1b with Docker Model Runner:
docker model run hf.co/google/vaultgemma-1b
not run
!pip install git+https://github.com/huggingface/transformers@v4.56.1-Vault-Gemma-preview
Collecting git+https://github.com/huggingface/transformers@v4.56.1-Vault-Gemma-preview
Cloning https://github.com/huggingface/transformers (to revision v4.56.1-Vault-Gemma-preview) to /tmp/pip-req-build-duush543
Running command git clone --filter=blob:none --quiet https://github.com/huggingface/transformers /tmp/pip-req-build-duush543
fatal: unable to access 'https://github.com/huggingface/transformers/': Could not resolve host: github.com
error: subprocess-exited-with-error
× git clone --filter=blob:none --quiet https://github.com/huggingface/transformers /tmp/pip-req-build-duush543 did not run successfully.
│ exit code: 128
╰─> See above for output.
note: This error originates from a subprocess, and is likely not a problem with pip.
error: subprocess-exited-with-error
× git clone --filter=blob:none --quiet https://github.com/huggingface/transformers /tmp/pip-req-build-duush543 did not run successfully.
│ exit code: 128
╰─> See above for output.
note: This error originates from a subprocess, and is likely not a problem with pip.
Note: you may need to restart the kernel to use updated packages.
Hi @wekW ,
Welcome to Gemma family of Google's open models, thanks for reaching out to us. I can successfully able to run the above given pip install in my local free Colab with T4 GPU. Please find the attached gist file for you reference. Please let me know if you required if any additional assistance is required.
Thanks.