Instructions to use google/paligemma2-10b-pt-448 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use google/paligemma2-10b-pt-448 with Transformers:

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

pipe = pipeline("image-text-to-text", model="google/paligemma2-10b-pt-448")

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("google/paligemma2-10b-pt-448")
model = AutoModelForMultimodalLM.from_pretrained("google/paligemma2-10b-pt-448")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use google/paligemma2-10b-pt-448 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "google/paligemma2-10b-pt-448"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "google/paligemma2-10b-pt-448",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/google/paligemma2-10b-pt-448

SGLang

How to use google/paligemma2-10b-pt-448 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/paligemma2-10b-pt-448" \
    --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/paligemma2-10b-pt-448",
		"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/paligemma2-10b-pt-448" \
        --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/paligemma2-10b-pt-448",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use google/paligemma2-10b-pt-448 with Docker Model Runner:
```
docker model run hf.co/google/paligemma2-10b-pt-448
```

Request: DOI

by hzg991022 - opened 2 days ago

Discussion

hzg991022

2 days ago

study and learn

sonali-kumari11

Google org 1 day ago

•

edited 1 day ago

Hi @hzg991022 -

If you need access to the model, please request access directly from the model card section on Hugging Face and use a valid access token to load the model locally. You can access the google/paligemma2-10b-pt-448 model using the granted access token or download the model weights for local use. For generating access token in HuggingFace, please refer to this documentation.

If you have any further questions related to this model, feel free to share more details. Thanks!

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment