Instructions to use ChatDOC/OCRFlux-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ChatDOC/OCRFlux-3B with Transformers:

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

pipe = pipeline("image-text-to-text", model="ChatDOC/OCRFlux-3B")
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 AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("ChatDOC/OCRFlux-3B")
model = AutoModelForImageTextToText.from_pretrained("ChatDOC/OCRFlux-3B")
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=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use ChatDOC/OCRFlux-3B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ChatDOC/OCRFlux-3B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ChatDOC/OCRFlux-3B",
		"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/ChatDOC/OCRFlux-3B

SGLang

How to use ChatDOC/OCRFlux-3B 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 "ChatDOC/OCRFlux-3B" \
    --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": "ChatDOC/OCRFlux-3B",
		"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 "ChatDOC/OCRFlux-3B" \
        --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": "ChatDOC/OCRFlux-3B",
		"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 ChatDOC/OCRFlux-3B with Docker Model Runner:
```
docker model run hf.co/ChatDOC/OCRFlux-3B
```

ChatDOC commited on Jun 12, 2025

Commit

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Update README.md

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README.md +33 -34

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@@ -1,34 +1,33 @@
----
-language:
-- en
-license: apache-2.0
-benchmarks:
-- ChatDoc/OCRFlux-bench-single
-- ChatDoc/OCRFlux-bench-cross
-- ChatDoc/OCRFlux-pubtabnet-single
-- ChatDoc/OCRFlux-pubtabnet-cross
-base_model:
-- Qwen/Qwen2.5-VL-3B-Instruct
-library_name: transformers
----
-<img alt="OCRFlux Logo" src="https://github.com/chatdoc-com/OCRFlux/blob/main/images/OCRFlux.png" width="242px" style="margin-left:'auto' margin-right:'auto' display:'block'">
-# OCRFlux
-This is a preview release of the OCRFlux model that's fine tuned from Qwen2.5-VL-3B-Instruct using the our private document datasets and some data from
-[olmOCR-mix-0225](https://huggingface.co/datasets/allenai/olmOCR-mix-0225) dataset.
-Quick links:
-- 🛠️ [Code](https://github.com/chatdoc-com/OCRFlux)
-## Usage
-The best way to use this model is via the [OCRFlux toolkit](https://github.com/chatdoc-com/OCRFlux).
-The toolkit comes with an efficient inference setup via vllm that can handle millions of documents
-at scale.
-## License and use
-OCRFlux is licensed under the Apache 2.0 license.
-OCRFlux is intended for research and educational use.

+---
+language:
+- en
+license: apache-2.0
+benchmarks:
+- ChatDoc/OCRFlux-bench-single
+- ChatDoc/OCRFlux-bench-cross
+- ChatDoc/OCRFlux-pubtabnet-single
+- ChatDoc/OCRFlux-pubtabnet-cross
+base_model:
+- Qwen/Qwen2.5-VL-3B-Instruct
+library_name: transformers
+---
+# OCRFlux
+This is a preview release of the OCRFlux model that's fine tuned from Qwen2.5-VL-3B-Instruct using the our private document datasets and some data from
+[olmOCR-mix-0225](https://huggingface.co/datasets/allenai/olmOCR-mix-0225) dataset.
+Quick links:
+- 🛠️ [Code](https://github.com/chatdoc-com/OCRFlux)
+## Usage
+The best way to use this model is via the [OCRFlux toolkit](https://github.com/chatdoc-com/OCRFlux).
+The toolkit comes with an efficient inference setup via vllm that can handle millions of documents
+at scale.
+## License and use
+OCRFlux is licensed under the Apache 2.0 license.
+OCRFlux is intended for research and educational use.