Instructions to use google/gemma-2-2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/gemma-2-2b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="google/gemma-2-2b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("google/gemma-2-2b") model = AutoModelForCausalLM.from_pretrained("google/gemma-2-2b") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use google/gemma-2-2b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "google/gemma-2-2b" # 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-2-2b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/google/gemma-2-2b
- SGLang
How to use google/gemma-2-2b 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-2-2b" \ --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-2-2b", "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-2-2b" \ --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-2-2b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use google/gemma-2-2b with Docker Model Runner:
docker model run hf.co/google/gemma-2-2b
Gemma 2 2b not authorized
After running python gemma_summarizer.py in cmd as an administrator, I get this message:
Token is valid (permission: fineGrained).
Your token has been saved in your configured git credential helpers (manager).
Your token has been saved to C:\Users\Kareena.cache\huggingface\token
Login successful
Error loading model or tokenizer: You are trying to access a gated repo.
Make sure to have access to it at https://huggingface.co/google/gemma-2-2b.
403 Client Error. (Request ID: Root=1-66f6e0f6-180b57b0346c2ac74fc99f5b;85aa7201-b854-47bc-a1ef-3d32475b9c28)
Cannot access gated repo for url https://huggingface.co/google/gemma-2-2b/resolve/main/config.json.
Access to model google/gemma-2-2b is restricted and you are not in the authorized list. Visit https://huggingface.co/google/gemma-2-2b to ask for access.
Not sure why. Any explanations?
This is gated repo model's permission error which can be resolved by providing the repo access token. You can create your HF_token by clicking on Settings - Access Tokens(left pane) - Create Token in HF site and pass this token value in your notebook by using below code line or by putting as a secret key in you Colab notebook.
from huggingface_hub import notebook_login
notebook_login()
You can also refer to this similar issue which may helpful to you in this.