Instructions to use Skywork/Skywork-R1V2-38B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Skywork/Skywork-R1V2-38B with Transformers:

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

pipe = pipeline("image-text-to-text", model="Skywork/Skywork-R1V2-38B", 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 AutoModel
model = AutoModel.from_pretrained("Skywork/Skywork-R1V2-38B", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Skywork/Skywork-R1V2-38B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Skywork/Skywork-R1V2-38B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Skywork/Skywork-R1V2-38B",
		"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/Skywork/Skywork-R1V2-38B

SGLang

How to use Skywork/Skywork-R1V2-38B 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 "Skywork/Skywork-R1V2-38B" \
    --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": "Skywork/Skywork-R1V2-38B",
		"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 "Skywork/Skywork-R1V2-38B" \
        --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": "Skywork/Skywork-R1V2-38B",
		"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 Skywork/Skywork-R1V2-38B with Docker Model Runner:
```
docker model run hf.co/Skywork/Skywork-R1V2-38B
```

OrlandoHugBot commited on Apr 22, 2025

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@@ -11,27 +11,20 @@ license: mit
 </div>
 ## 📖 [Technical Report](https://github.com/SkyworkAI/Skywork-R1V/blob/main/Skywork_R1V.pdf) | 💻 [GitHub](https://github.com/SkyworkAI/Skywork-R1V) | 🌐 [ModelScope](https://modelscope.cn/models/Skywork/Skywork-R1V-38B)
 <div align="center">
 [![GitHub Stars](https://img.shields.io/github/stars/SkyworkAI/Skywork-R1V)](https://github.com/SkyworkAI/Skywork-R1V/stargazers) [![GitHub Forks](https://img.shields.io/github/forks/SkyworkAI/Skywork-R1V)](https://github.com/SkyworkAI/Skywork-R1V/fork)
 </div>
 ## 1. Model Introduction
 Skywork-R1V2-38B is a **state-of-the-art open-source multimodal reasoning model**, achieving top-tier performance across multiple benchmarks:
 - On **MMMU**, it scores **73.6%**, the **highest among all open-source models** to date.
 - On **OlympiadBench**, it achieves **62.6%**, leading **by a large margin** over other open models.
 - R1V2 also performs strongly on **MathVision**, **MMMU-Pro**, and **MathVista**, **rivaling proprietary commercial models**.
 - Overall, R1V2 stands out as a **high-performing, open-source VLM** combining powerful **visual reasoning** and **text understanding**.
-<br>
 ### 🔧 Model Details
 <table>
   <thead>
     <tr>
@@ -52,6 +45,8 @@ Skywork-R1V2-38B is a **state-of-the-art open-source multimodal reasoning model*
 </table>
 ## 2. Evaluation

 </div>
 ## 📖 [Technical Report](https://github.com/SkyworkAI/Skywork-R1V/blob/main/Skywork_R1V.pdf) | 💻 [GitHub](https://github.com/SkyworkAI/Skywork-R1V) | 🌐 [ModelScope](https://modelscope.cn/models/Skywork/Skywork-R1V-38B)
 <div align="center">
 [![GitHub Stars](https://img.shields.io/github/stars/SkyworkAI/Skywork-R1V)](https://github.com/SkyworkAI/Skywork-R1V/stargazers) [![GitHub Forks](https://img.shields.io/github/forks/SkyworkAI/Skywork-R1V)](https://github.com/SkyworkAI/Skywork-R1V/fork)
 </div>
 ## 1. Model Introduction
 Skywork-R1V2-38B is a **state-of-the-art open-source multimodal reasoning model**, achieving top-tier performance across multiple benchmarks:
 - On **MMMU**, it scores **73.6%**, the **highest among all open-source models** to date.
 - On **OlympiadBench**, it achieves **62.6%**, leading **by a large margin** over other open models.
 - R1V2 also performs strongly on **MathVision**, **MMMU-Pro**, and **MathVista**, **rivaling proprietary commercial models**.
 - Overall, R1V2 stands out as a **high-performing, open-source VLM** combining powerful **visual reasoning** and **text understanding**.
 ### 🔧 Model Details
 <table>
   <thead>
     <tr>
 </table>
+---
 ## 2. Evaluation