Instructions to use hustvl/mmMamba-linear with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use hustvl/mmMamba-linear with Transformers:

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

pipe = pipeline("image-text-to-text", model="hustvl/mmMamba-linear", 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 AutoModel
model = AutoModel.from_pretrained("hustvl/mmMamba-linear", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use hustvl/mmMamba-linear with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "hustvl/mmMamba-linear"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "hustvl/mmMamba-linear",
		"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/hustvl/mmMamba-linear

SGLang

How to use hustvl/mmMamba-linear 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 "hustvl/mmMamba-linear" \
    --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": "hustvl/mmMamba-linear",
		"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 "hustvl/mmMamba-linear" \
        --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": "hustvl/mmMamba-linear",
		"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 hustvl/mmMamba-linear with Docker Model Runner:
```
docker model run hf.co/hustvl/mmMamba-linear
```

nielsr HF Staff commited on Feb 19, 2025

Commit

51a65d8

verified ·

1 Parent(s): 9598d88

Add metadata tags and link to code

Browse files

This PR adds the relevant metadata (library name and pipeline tag) to the model card. It also adds a link to the Github repository.

Files changed (1) hide show

README.md +6 -2

README.md CHANGED Viewed

@@ -1,6 +1,9 @@
 ---
 license: mit
 ---
 # mmMamba-linear Model Card
 ## Introduction
@@ -11,11 +14,13 @@ Distilled from the decoder-only HoVLE-2.6B, our pure Mamba-2-based mmMamba-linea
 <div align="center">
 <img src="teaser.png" />
 <b>Seeding strategy and three-stage distillation pipeline of mmMamba.</b>
 <img src="pipeline.png" />
 </div>
 ## Quick Start Guide for mmMamba Inference
 We provide example code to run mmMamba inference using the Transformers library.
@@ -41,7 +46,6 @@ Below are the primary dependencies required for model inference:
 - decord
 - seaborn
 ### Inference with Transformers
 ```python

 ---
 license: mit
+library_name: transformers
+pipeline_tag: image-text-to-text
 ---
 # mmMamba-linear Model Card
 ## Introduction
 <div align="center">
 <img src="teaser.png" />
 <b>Seeding strategy and three-stage distillation pipeline of mmMamba.</b>
 <img src="pipeline.png" />
 </div>
+Paper: [](https://hf.co/papers/2502.13145)
+Code: https://github.com/Hongyuan-Tao/mmMamba
 ## Quick Start Guide for mmMamba Inference
 We provide example code to run mmMamba inference using the Transformers library.
 - decord
 - seaborn
 ### Inference with Transformers
 ```python