Instructions to use XiaomiMiMo/MiMo-VL-7B-SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use XiaomiMiMo/MiMo-VL-7B-SFT with Transformers:

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

pipe = pipeline("image-text-to-text", model="XiaomiMiMo/MiMo-VL-7B-SFT")
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)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("XiaomiMiMo/MiMo-VL-7B-SFT")
model = AutoModelForMultimodalLM.from_pretrained("XiaomiMiMo/MiMo-VL-7B-SFT", 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=256)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use XiaomiMiMo/MiMo-VL-7B-SFT with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "XiaomiMiMo/MiMo-VL-7B-SFT"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "XiaomiMiMo/MiMo-VL-7B-SFT",
		"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/XiaomiMiMo/MiMo-VL-7B-SFT

SGLang

How to use XiaomiMiMo/MiMo-VL-7B-SFT 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 "XiaomiMiMo/MiMo-VL-7B-SFT" \
    --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": "XiaomiMiMo/MiMo-VL-7B-SFT",
		"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 "XiaomiMiMo/MiMo-VL-7B-SFT" \
        --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": "XiaomiMiMo/MiMo-VL-7B-SFT",
		"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 XiaomiMiMo/MiMo-VL-7B-SFT with Docker Model Runner:
```
docker model run hf.co/XiaomiMiMo/MiMo-VL-7B-SFT
```

Add pipeline tag and link to code

by nielsr HF Staff - opened Jun 6, 2025

base: refs/heads/main

←

from: refs/pr/2

Discussion Files changed

-4

Files changed (1) hide show

README.md +7 -4

README.md CHANGED Viewed

@@ -1,9 +1,11 @@
 ---
-license: mit
-library_name: transformers
 base_model:
 - XiaomiMiMo/MiMo-VL-7B-SFT
 ---
 <div align="center">
   <picture>
     <source srcset="https://github.com/XiaomiMiMo/MiMo-VL/raw/main/figures/Xiaomi_MiMo_darkmode.png?raw=true" media="(prefers-color-scheme: dark)">
@@ -32,6 +34,8 @@ base_model:
   &nbsp;|
   <a href="https://github.com/XiaomiMiMo/MiMo-VL/blob/main/MiMo-VL-Technical-Report.pdf" target="_blank">📔 Technical Report</a>
   &nbsp;|
   <br/>
 </div>
@@ -127,7 +131,6 @@ The MiMo-VL-7B series maintain full compatibility with the `Qwen2_5_VLForConditi
 }
 ```
 ## VI. Contact
-Please contact us at [mimo@xiaomi.com](mailto:mimo@xiaomi.com) or open an issue if you have any questions.

 ---
 base_model:
 - XiaomiMiMo/MiMo-VL-7B-SFT
+library_name: transformers
+license: mit
+pipeline_tag: image-text-to-text
 ---
 <div align="center">
   <picture>
     <source srcset="https://github.com/XiaomiMiMo/MiMo-VL/raw/main/figures/Xiaomi_MiMo_darkmode.png?raw=true" media="(prefers-color-scheme: dark)">
   &nbsp;|
   <a href="https://github.com/XiaomiMiMo/MiMo-VL/blob/main/MiMo-VL-Technical-Report.pdf" target="_blank">📔 Technical Report</a>
   &nbsp;|
+  <a href="https://github.com/XiaomiMiMo/MiMo-VL" target="_blank">💻 Github Repo</a>
+  &nbsp;|
   <br/>
 </div>
 }
 ```
 ## VI. Contact
+Please contact us at [mimo@xiaomi.com](mailto:mimo@xiaomi.com) or open an issue if you have any questions.