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")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("ibm-granite/granite-4.0-3b-vision", dtype="auto")

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/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ibm-granite/granite-4.0-3b-vision",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ibm-granite/granite-4.0-3b-vision",
		"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 "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/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ibm-granite/granite-4.0-3b-vision",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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
```

when gguf???

by VivekLeon - opened Apr 1

Discussion

VivekLeon

Apr 1

when gguf???

gabegoodhart

IBM Granite org Apr 1

Hi @VivekLeon ! llama.cpp and GGUF support is definitely on the TODO list. Since this model uses an adapter to conditionally support vision inputs, there will be some architectural changes needed in the mtmd layer of llama.cpp so that the adapter is only activated when image inputs are present. This will also mean that other engines such as Ollama may need similar changes, so the rollout of GGUF support will be a bit slower than some other model architectures unfortunately.

julien-c

Apr 1

agree it could be awesome!!

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