Instructions to use dots-studio/dots.mocr-svg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use dots-studio/dots.mocr-svg with Transformers:

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

pipe = pipeline("image-text-to-text", model="dots-studio/dots.mocr-svg", 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 AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("dots-studio/dots.mocr-svg", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use dots-studio/dots.mocr-svg with vLLM:

Install from pip and serve model

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

SGLang

How to use dots-studio/dots.mocr-svg 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 "dots-studio/dots.mocr-svg" \
    --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": "dots-studio/dots.mocr-svg",
		"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 "dots-studio/dots.mocr-svg" \
        --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": "dots-studio/dots.mocr-svg",
		"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 dots-studio/dots.mocr-svg with Docker Model Runner:
```
docker model run hf.co/dots-studio/dots.mocr-svg
```

ygfrancois commited on Mar 20

Commit

1ad41be

verified ·

1 Parent(s): 0ab24b6

Upload README.md with huggingface_hub

Browse files

Files changed (1) hide show

README.md +4 -4

README.md CHANGED Viewed

@@ -566,7 +566,7 @@ cd dots.mocr
 pip install -e .
 ```
-If you have trouble with the installation, try our [Docker Image](https://hub.docker.com/r/rednotehilab/dots.ocr) for an easier setup, and follow these steps:
 ### Download Model Weights
@@ -581,15 +581,15 @@ python3 tools/download_model.py --type modelscope
 ## 2. Deployment
 ### vLLM inference
-We highly recommend using vLLM for deployment and inference. **Since vLLM version 0.11.0, Dots OCR has been officially integrated into vLLM with verified performance** and you can use vLLM docker image directly (e.g, `vllm/vllm-openai:v0.11.0`) to deploy the model server.
 ```shell
 # Launch vLLM model server
 ## dots.mocr
-CUDA_VISIBLE_DEVICES=0 vllm serve rednote-hilab/dots.mocr --tensor-parallel-size 1 --gpu-memory-utilization 0.9 --chat-template-content-format string --served-model-name model --trust-remote-code
 ## dots.mocr-svg
-CUDA_VISIBLE_DEVICES=0 vllm serve rednote-hilab/dots.mocr-svg --tensor-parallel-size 1 --gpu-memory-utilization 0.9 --chat-template-content-format string --served-model-name model --trust-remote-code
 # vLLM API Demo
 # See dots_mocr/model/inference.py and dots_mocr/utils/prompts.py for details on parameter and prompt settings

 pip install -e .
 ```
+If you have trouble with the installation, we recommend to use vLLM inference. Try official vLLM [Docker Image](https://hub.docker.com/layers/vllm/vllm-openai/v0.17.1-cu130/images/sha256-ec9b626d16b2af377662d9d31c1784aac5174b571450a1e25ffd90ddb639f2d2) for an easier setup, and follow these steps:
 ### Download Model Weights
 ## 2. Deployment
 ### vLLM inference
+We highly recommend using vLLM for deployment and inference. **Since vLLM version 0.11.0, Dots OCR has been officially integrated into vLLM with verified performance** and you can use vLLM docker image directly (e.g, `vllm/vllm-openai:v0.17.1`) to deploy the model server.
 ```shell
 # Launch vLLM model server
 ## dots.mocr
+CUDA_VISIBLE_DEVICES=0 vllm serve rednote-hilab/dots.mocr --tensor-parallel-size 1 --gpu-memory-utilization 0.9 --chat-template-content-format string --trust-remote-code
 ## dots.mocr-svg
+CUDA_VISIBLE_DEVICES=0 vllm serve rednote-hilab/dots.mocr-svg --tensor-parallel-size 1 --gpu-memory-utilization 0.9 --chat-template-content-format string --trust-remote-code
 # vLLM API Demo
 # See dots_mocr/model/inference.py and dots_mocr/utils/prompts.py for details on parameter and prompt settings