Instructions to use zenosai/MonkeyOCRv2-B-Und with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use zenosai/MonkeyOCRv2-B-Und with Transformers:

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

pipe = pipeline("image-text-to-text", model="zenosai/MonkeyOCRv2-B-Und", 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("zenosai/MonkeyOCRv2-B-Und", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use zenosai/MonkeyOCRv2-B-Und with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zenosai/MonkeyOCRv2-B-Und"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zenosai/MonkeyOCRv2-B-Und",
		"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/zenosai/MonkeyOCRv2-B-Und

SGLang

How to use zenosai/MonkeyOCRv2-B-Und 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 "zenosai/MonkeyOCRv2-B-Und" \
    --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": "zenosai/MonkeyOCRv2-B-Und",
		"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 "zenosai/MonkeyOCRv2-B-Und" \
        --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": "zenosai/MonkeyOCRv2-B-Und",
		"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 zenosai/MonkeyOCRv2-B-Und with Docker Model Runner:
```
docker model run hf.co/zenosai/MonkeyOCRv2-B-Und
```

Improve model card: Add transformers library tag, paper/code links, authors, and fix image URLs

by nielsr HF Staff - opened 2 days ago

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+15

-9

nielsr

2 days ago

This PR improves the model card for MonkeyOCRv2 by:

Adding the library_name: transformers tag to the metadata. This will enable the "Use in Transformers" button on the top right of the model page, making it easier for users to load the model and providing an automated code snippet.
Explicitly listing the Paper, Code (main GitHub repository), and Authors for better readability and discoverability, in addition to the existing badges.
Correcting the URL for the "Text detection results" image from overview.png to text_detection.png and ensuring all raw GitHub image links use the raw.githubusercontent.com domain for robustness and consistency.

Improve model card: Add transformers library tag, paper/code links, authors, and fix image URLs512ea804

zenosai

Owner 1 day ago

Thanks for your contribution!

zenosai changed pull request status to merged 1 day ago

zenosai deleted the refs/pr/1 ref 1 day ago

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