Instructions to use google/gemma-2-27b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/gemma-2-27b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="google/gemma-2-27b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("google/gemma-2-27b") model = AutoModelForCausalLM.from_pretrained("google/gemma-2-27b") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use google/gemma-2-27b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "google/gemma-2-27b" # 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-2-27b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/google/gemma-2-27b
- SGLang
How to use google/gemma-2-27b 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-2-27b" \ --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-2-27b", "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-2-27b" \ --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-2-27b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use google/gemma-2-27b with Docker Model Runner:
docker model run hf.co/google/gemma-2-27b
Inquiry on Minimum Configuration and Cost for Running Gemma-2-27B Model Efficiently
I am interested in running the Gemma-2-27B model and would like to inquire about the minimum hardware configuration required to achieve fast and immediate responses. Additionally, could you please provide an estimate of the associated costs for operating the model under these conditions?
Hi @ltkien2003 ,
The Gemma-2-27B model is optimized to run inference efficiently at full precision on a single Google Cloud TPU host, NVIDIA A100 80GB Tensor Core GPU, or NVIDIA H100 Tensor Core GPU. This approach significantly reduces costs while preserving high performance, making AI deployments more accessible and budget-friendly.
Please refer to the Gemma2 blog: https://blog.google/technology/developers/google-gemma-2/ for more details.
Regarding additional costs, it totally depends on where you are running the model for inference, whether locally or on some cloud compute.
Thank you.