Instructions to use tencent/HunyuanOCR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tencent/HunyuanOCR with Transformers:

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

pipe = pipeline("image-text-to-text", model="tencent/HunyuanOCR")
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 AutoModelForSeq2SeqLM
model = AutoModelForSeq2SeqLM.from_pretrained("tencent/HunyuanOCR", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use tencent/HunyuanOCR with vLLM:

Install from pip and serve model

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

SGLang

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

Update README

#14

by EthannW - opened Nov 27, 2025

base: refs/heads/main

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@@ -201,6 +201,15 @@ print(clean_repeated_substrings(output.outputs[0].text))
 | **Information Extraction** | • Output the value of Key.<br><br>• Extract the content of the fields: ['key1','key2', ...] from the image and return it in JSON format.<br><br>• Extract the subtitles from the image. | • 输出 Key 的值。<br><br>• 提取图片中的: ['key1','key2', ...] 的字段内容，并按照 JSON 格式返回。<br><br>• 提取图片中的字幕。 |
 | **Translation** | First extract the text, then translate the text content into English. If it is a document, ignore the header and footer. Formulas should be represented in LaTeX format, and tables should be represented in HTML format. | 先提取文字，再将文字内容翻译为英文。若是文档，则其中页眉、页脚忽略。公式用latex格式表示，表格用html格式表示。 |
 ## 📚 Citation
 ```

 | **Information Extraction** | • Output the value of Key.<br><br>• Extract the content of the fields: ['key1','key2', ...] from the image and return it in JSON format.<br><br>• Extract the subtitles from the image. | • 输出 Key 的值。<br><br>• 提取图片中的: ['key1','key2', ...] 的字段内容，并按照 JSON 格式返回。<br><br>• 提取图片中的字幕。 |
 | **Translation** | First extract the text, then translate the text content into English. If it is a document, ignore the header and footer. Formulas should be represented in LaTeX format, and tables should be represented in HTML format. | 先提取文字，再将文字内容翻译为英文。若是文档，则其中页眉、页脚忽略。公式用latex格式表示，表格用html格式表示。 |
+## 🤝 Join Our Community
+<div align="center">
+| Wechat Discussion Group | Discord Group |
+| :---: | :---: |
+| <img src="./assets/qrcode_for_hunyuanocr_wechat.jpg" width="150"> | [Join HunyuanOCR Discord](https://discord.gg/XeD3p2MRDk) |
+</div>
 ## 📚 Citation
 ```