Instructions to use google/gemma-2-2b-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use google/gemma-2-2b-it with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="google/gemma-2-2b-it")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("google/gemma-2-2b-it")
model = AutoModelForCausalLM.from_pretrained("google/gemma-2-2b-it")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.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(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use google/gemma-2-2b-it 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-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-2-2b-it",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/google/gemma-2-2b-it

SGLang

How to use google/gemma-2-2b-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-2-2b-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-2-2b-it",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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-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-2-2b-it",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use google/gemma-2-2b-it with Docker Model Runner:
```
docker model run hf.co/google/gemma-2-2b-it
```

torch.compile error

#47

by LD-inform - opened Oct 31, 2024

Discussion

LD-inform

Oct 31, 2024

•

edited Oct 31, 2024

Hi, i have this problem when i am running torch.compile code snippet:

Traceback (most recent call last):
File "/data/gemma_torch/torch_compile.py", line 40, in
outputs = model.generate(**model_inputs, past_key_values=past_key_values, do_sample=True, temperature=1.0, max_new_tokens=128)
...
torch._dynamo.exc.Unsupported: reconstruct: UserDefinedObjectVariable(HybridCache)
from user code:
File "/home/.local/lib/python3.10/site-packages/transformers/models/gemma2/modeling_gemma2.py", line 1111, in forward
return CausalLMOutputWithPast(

Versions:
torch: 2.3.1
transformers 4.42.4
python: 3.10
Cuda compilation tools, release 12.2, V12.2.140
Build cuda_12.2.r12.2/compiler.33191640_0

GPU: NVIDIA L40S

Did anyone encounter this problem? What can i try to get it running?

Renu11

Google org Nov 4, 2024

•

edited Nov 4, 2024

Hi @LD-inform , It seems, there is issue with the installed torch version 2.3.1 . Could you please try again by upgrading the torch library to the latest version 2.5.1 using !pip install -U torch and let us know if the issue still persists.

LD-inform

Nov 12, 2024

•

edited Nov 13, 2024

Thank you @Renu11 .

i had to add this parameter to torch.compile(..., backend="eager")
without it, i had this error:

/.local/lib/python3.10/site-packages/torch/_dynamo/output_graph.py", line 1465, in _call_user_compiler
raise BackendCompilerFailed(self.compiler_fn, e) from e
torch._dynamo.exc.BackendCompilerFailed: backend='inductor' raised:
RuntimeError: Should never be installed

however, the speed increased only by 5t/s (from 44t/s to 49t/s) in 2B model and in 9B model it even decreased from 26t/s to 20t/s.

i used it with different prompt as well but i doubt that is the problem:
input_text = "user\nExplain in details difference between integrals and derivatives.\nmodel"

is there anything else i can try?

Renu11

Google org Jul 25, 2025

Apologies for the delayed response. I tried replicating the same issue and found that it's been resolved in the latest versions of the transformers and torch libraries. Could you please confirm if you're still encountering this problem after updating your libraries? Thank you.

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