Instructions to use google/gemma-2-9b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/gemma-2-9b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="google/gemma-2-9b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("google/gemma-2-9b") model = AutoModelForCausalLM.from_pretrained("google/gemma-2-9b") - Inference
- Local Apps Settings
- vLLM
How to use google/gemma-2-9b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "google/gemma-2-9b" # 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-2-9b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/google/gemma-2-9b
- SGLang
How to use google/gemma-2-9b 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-2-9b" \ --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-2-9b", "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-2-9b" \ --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-2-9b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use google/gemma-2-9b with Docker Model Runner:
docker model run hf.co/google/gemma-2-9b
TypeError: arange() received an invalid combination of arguments
TypeError: arange() received an invalid combination of arguments - got (NoneType, int, device=torch.device), but expected one of:
- (Number end, *, Tensor out, torch.dtype dtype, torch.layout layout, torch.device device, bool pin_memory, bool requires_grad)
- (Number start, Number end, *, torch.dtype dtype, torch.layout layout, torch.device device, bool pin_memory, bool requires_grad)
- (Number start, Number end, Number step, *, Tensor out, torch.dtype dtype, torch.layout layout, torch.device device, bool pin_memory, bool requires_grad)
I got this error when I was running the code "outputs = model.generate(**input_ids)"
I ran into the same problem before. The error message was misleading, and it turned out to be related to a dependent library of transformers.
You can try with these lib dependencies (https://github.com/huggingface/alignment-handbook/blob/main/setup.py) along with the latest transformers in the repo.
Hey @darrenbudiman , @tanliboy , sorry you ran in this issue!
@tanliboy do you mind sharing what was the issue with a dependent library? We should try to solve this.
@lysandre I took a closer look at the issue, and here's what I found. I initially thought it was a dependency problem. However, I found it was related to a bug in transformers (see issue #31664). This bug has already been fixed in PR #31661.
It is worth noting that the Gemma 2 PR #31659 landed a few hours before this PR. If anyone pulled the master version between them, they might encounter this problem.
Hi @darrenbudiman , @tanliboy , I hope the issue has been resolved. Please let us know if any further assistance is needed. Thanks!