Instructions to use google/paligemma-3b-pt-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use google/paligemma-3b-pt-224 with Transformers:

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

pipe = pipeline("image-text-to-text", model="google/paligemma-3b-pt-224")

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("google/paligemma-3b-pt-224")
model = AutoModelForImageTextToText.from_pretrained("google/paligemma-3b-pt-224")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use google/paligemma-3b-pt-224 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "google/paligemma-3b-pt-224"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "google/paligemma-3b-pt-224",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/google/paligemma-3b-pt-224

SGLang

How to use google/paligemma-3b-pt-224 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/paligemma-3b-pt-224" \
    --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/paligemma-3b-pt-224",
		"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/paligemma-3b-pt-224" \
        --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/paligemma-3b-pt-224",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use google/paligemma-3b-pt-224 with Docker Model Runner:
```
docker model run hf.co/google/paligemma-3b-pt-224
```

ValueError: Custom 4D attention mask should be passed in inverted form with max==0

#12

by brian-gordon - opened Jun 2, 2024

Discussion

brian-gordon

Google org Jun 2, 2024

Hi,

I am trying to use the code by running the example code snippet in the Model Card.. but I am receiving the following error:

Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
  File "/opt/conda/envs/paligemma-hf/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/opt/conda/envs/paligemma-hf/lib/python3.10/site-packages/transformers/generation/utils.py", line 1824, in generate
    result = self._sample(
  File "/opt/conda/envs/paligemma-hf/lib/python3.10/site-packages/transformers/generation/utils.py", line 2463, in _sample
    outputs = self(
  File "/opt/conda/envs/paligemma-hf/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/opt/conda/envs/paligemma-hf/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/opt/conda/envs/paligemma-hf/lib/python3.10/site-packages/transformers/models/paligemma/modeling_paligemma.py", line 468, in forward
    outputs = self.language_model(
  File "/opt/conda/envs/paligemma-hf/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/opt/conda/envs/paligemma-hf/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/opt/conda/envs/paligemma-hf/lib/python3.10/site-packages/transformers/models/gemma/modeling_gemma.py", line 1113, in forward
    outputs = self.model(
  File "/opt/conda/envs/paligemma-hf/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/opt/conda/envs/paligemma-hf/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/opt/conda/envs/paligemma-hf/lib/python3.10/site-packages/transformers/models/gemma/modeling_gemma.py", line 883, in forward
    causal_mask = self._update_causal_mask(
  File "/opt/conda/envs/paligemma-hf/lib/python3.10/site-packages/transformers/models/gemma/modeling_gemma.py", line 1003, in _update_causal_mask
    raise ValueError("Custom 4D attention mask should be passed in inverted form with max==0`")
ValueError: Custom 4D attention mask should be passed in inverted form with max==0`

The shapes of model_inputs are:

input_ids torch.Size([1, 260])
attention_mask torch.Size([1, 260])
pixel_values torch.Size([1, 3, 224, 224])

Details of my environment:

Python version: 3.10.14
CUDA hardware: GPU A100
CUDA version: 12.0
Torch version: 2.3.0
Transformers version: 4.42.0.dev0

Note: Having the same versions, but with a CUDA hardware V100, I don't have this issue

Saee

Jun 8, 2024

Hi @brian-gordon , I came across the same issue while running paligemma model for vQA. Here https://github.com/huggingface/transformers/issues/31171#issuecomment-2145421881 it is mentioned it is a regression due to a merge which will be fixed. You can solve it for now by pinning the transformers library version to 4.41.1.

lkv

Google org Jan 7, 2025

Hi @brian-gordon , Could you please refer this similar issue for paligemma inverted mask. and also PR is merged, added the mask inversion in this update PR. Kindly follow this and let me know if you have any concerns.

Thank you.

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