Instructions to use microsoft/Mage-VL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use microsoft/Mage-VL with Transformers:

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

pipe = pipeline("image-text-to-text", model="microsoft/Mage-VL", 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 AutoModelForImageTextToText
model = AutoModelForImageTextToText.from_pretrained("microsoft/Mage-VL", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use microsoft/Mage-VL with vLLM:

Install from pip and serve model

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

SGLang

How to use microsoft/Mage-VL 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 "microsoft/Mage-VL" \
    --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": "microsoft/Mage-VL",
		"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 "microsoft/Mage-VL" \
        --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": "microsoft/Mage-VL",
		"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 microsoft/Mage-VL with Docker Model Runner:
```
docker model run hf.co/microsoft/Mage-VL
```

Mage-VL

File size: 3,243 Bytes

12acbba

{
  "auto_map": {
    "AutoConfig": "configuration_mage_vl.MageVLConfig",
    "AutoModel": "modeling_mage_vl.MageVLModel",
    "AutoModelForImageTextToText": "modeling_mage_vl.MageVLForConditionalGeneration",
    "AutoProcessor": "processing_mage_vl.MageVLProcessor",
    "AutoVideoProcessor": "video_processing_mage_vl.MageVLVideoProcessor",
    "AutoModelForCausalLM": "modeling_mage_vl.MageVLForConditionalGeneration"
  },
  "dtype": "bfloat16",
  "image_token_id": 151655,
  "model_type": "mage_vl",
  "text_config": {
    "_name_or_path": "/mage-vl/pretrain_models/Qwen3-4B-Instruct-2507",
    "architectures": [
      "MageVLForConditionalGeneration"
    ],
    "attention_bias": false,
    "attention_dropout": 0.0,
    "bos_token_id": 151643,
    "dtype": "bfloat16",
    "eos_token_id": 151645,
    "head_dim": 128,
    "hidden_act": "silu",
    "hidden_size": 2560,
    "initializer_range": 0.02,
    "intermediate_size": 9728,
    "layer_types": [
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    "max_position_embeddings": 262144,
    "max_window_layers": 36,
    "model_type": "qwen3",
    "num_attention_heads": 32,
    "num_hidden_layers": 36,
    "num_key_value_heads": 8,
    "rms_norm_eps": 1e-06,
    "rope_scaling": null,
    "sliding_window": null,
    "use_cache": true,
    "use_sliding_window": false,
    "vocab_size": 151936,
    "rope_parameters": {
      "rope_theta": 5000000,
      "rope_type": "default"
    },
    "tie_word_embeddings": false
  },
  "transformers_version": "5.7.0",
  "video_token_id": 151656,
  "vision_config": {
    "attention_dropout": 0.0,
    "frame_windows_size": 4,
    "hidden_act": "gelu",
    "hidden_size": 1024,
    "image_size": 448,
    "initializer_range": 0.02,
    "intermediate_size": 4096,
    "layer_norm_eps": 1e-06,
    "layer_norm_type": "layer_norm",
    "model_type": "mage_vl_vision",
    "num_attention_heads": 16,
    "num_channels": 3,
    "num_hidden_layers": 24,
    "out_hidden_size": 2560,
    "patch_size": 16,
    "rope_theta": 10000.0,
    "spatial_merge_size": 2,
    "temporal_patch_size": 1,
    "text_hidden_size": 2560,
    "tokens_per_second": 1,
    "use_head": false,
    "max_position_embeddings": 8192
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "architectures": [
    "MageVLForConditionalGeneration"
  ],
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "tie_word_embeddings": false
}