Instructions to use ibm-granite/granite-4.0-3b-vision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ibm-granite/granite-4.0-3b-vision with Transformers:

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

pipe = pipeline("image-text-to-text", model="ibm-granite/granite-4.0-3b-vision", trust_remote_code=True)
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("ibm-granite/granite-4.0-3b-vision", trust_remote_code=True)
model = AutoModelForMultimodalLM.from_pretrained("ibm-granite/granite-4.0-3b-vision", trust_remote_code=True, device_map="auto")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.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(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ibm-granite/granite-4.0-3b-vision with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ibm-granite/granite-4.0-3b-vision"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ibm-granite/granite-4.0-3b-vision",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/ibm-granite/granite-4.0-3b-vision

SGLang

How to use ibm-granite/granite-4.0-3b-vision 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 "ibm-granite/granite-4.0-3b-vision" \
    --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": "ibm-granite/granite-4.0-3b-vision",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "ibm-granite/granite-4.0-3b-vision" \
        --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": "ibm-granite/granite-4.0-3b-vision",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use ibm-granite/granite-4.0-3b-vision with Docker Model Runner:
```
docker model run hf.co/ibm-granite/granite-4.0-3b-vision
```

Docker error The size of tensor a (1280) must match the size of tensor b (2560) at non-singleton dimension 1

by kuopching - opened Apr 7

Discussion

kuopching

Apr 7

Hi, i have trouble to run ibm-granite/granite-4.0-3b-vision using docker.

vllm version: 0.19.0
command:
docker run --gpus all -p 9999:8000 --ipc=host vllm-granite-vision --model ibm-granite/granite-4.0-3b-vision --trust-remote-code --max-model-len 16384 --tens
or-parallel-size 2 --host 0.0.0.0 --port 8000 --hf-overrides '{"adapter_path": "ibm-granite/granite-4.0-3b-vision"}' --gpu-memory-utilization 0.7

error:
(Worker_TP1 pid=83) ERROR 04-07 07:26:04 [multiproc_executor.py:857] loaded_weights = model.load_weights(self.get_all_weights(model_config, model))
(Worker_TP1 pid=83) ERROR 04-07 07:26:04 [multiproc_executor.py:857] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP1 pid=83) ERROR 04-07 07:26:04 [multiproc_executor.py:857] File "/app/granite4_vision.py", line 948, in load_weights
(Worker_TP1 pid=83) ERROR 04-07 07:26:04 [multiproc_executor.py:857] self._apply_adapter()
(Worker_TP1 pid=83) ERROR 04-07 07:26:04 [multiproc_executor.py:857] File "/app/granite4_vision.py", line 940, in _apply_adapter
(Worker_TP1 pid=83) ERROR 04-07 07:26:04 [multiproc_executor.py:857] n = self._merge_lora_deltas(adapter_config, adapter_weights)
(Worker_TP1 pid=83) ERROR 04-07 07:26:04 [multiproc_executor.py:857] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP1 pid=83) ERROR 04-07 07:26:04 [multiproc_executor.py:857] File "/app/granite4_vision.py", line 919, in _merge_lora_deltas
(Worker_TP1 pid=83) ERROR 04-07 07:26:04 [multiproc_executor.py:857] if _add_delta(module_key + ".weight", delta):
(Worker_TP1 pid=83) ERROR 04-07 07:26:04 [multiproc_executor.py:857] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP1 pid=83) ERROR 04-07 07:26:04 [multiproc_executor.py:857] File "/app/granite4_vision.py", line 906, in _add_delta
(Worker_TP1 pid=83) ERROR 04-07 07:26:04 [multiproc_executor.py:857] param.data = (param.data.float() + delta.to(param.device)).to(param.dtype)
(Worker_TP1 pid=83) ERROR 04-07 07:26:04 [multiproc_executor.py:857] ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
(Worker_TP1 pid=83) ERROR 04-07 07:26:04 [multiproc_executor.py:857] RuntimeError: The size of tensor a (1280) must match the size of tensor b (2560) at non-singleton dimension 1

artemspector

IBM Granite org Apr 9

Hi, there might be an issue with handling tensor parallelism in case of full merge flow. I'm going to check it.
Meanwhile you can try the inference on a single GPU by removing the command arg --tensor-parallel-size 2

artemspector

IBM Granite org Apr 12

Pushed the fixed version, should work now with multiple GPUs

artemspector changed discussion status to closed Apr 12

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