Instructions to use Skywork/Skywork-R1V-38B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Skywork/Skywork-R1V-38B with Transformers:

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

pipe = pipeline("image-text-to-text", model="Skywork/Skywork-R1V-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-R1V-38B", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Skywork/Skywork-R1V-38B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Skywork/Skywork-R1V-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-R1V-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-R1V-38B

SGLang

How to use Skywork/Skywork-R1V-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-R1V-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-R1V-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-R1V-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-R1V-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-R1V-38B with Docker Model Runner:
```
docker model run hf.co/Skywork/Skywork-R1V-38B
```

shawn0wang commited on Mar 17, 2025

Commit

0685b31

verified ·

1 Parent(s): ae509db

Update README.md

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Files changed (1) hide show

README.md +7 -7

README.md CHANGED Viewed

@@ -69,7 +69,7 @@ The model follows a connection pattern of Vision Encoder → MLP Adapter → Lan
     <tr>
       <td>Qwen2.5-72B-Instruct</td>
       <td align="center">❌</td>
-      <td align="center">82.6</td>
       <td align="center">23.3</td>
       <td align="center">49.0</td>
       <td align="center">-</td>
@@ -99,15 +99,15 @@ The model follows a connection pattern of Vision Encoder → MLP Adapter → Lan
       <td align="center">78.3</td>
       <td align="center">16.0</td>
       <td align="center">65.0</td>
-      <td align="center">67.7</td>
-      <td align="center">68.3</td>
     </tr>
     <tr>
       <td>GPT-4o</td>
       <td align="center">✅</td>
-      <td align="center">76.6</td>
       <td align="center">9.3</td>
-      <td align="center">53.6</td>
       <td align="center">63.8</td>
       <td align="center">69.1</td>
     </tr>
@@ -145,7 +145,7 @@ The model follows a connection pattern of Vision Encoder → MLP Adapter → Lan
       <td align="center">-</td>
       <td align="center">-</td>
       <td align="center">65.5</td>
-      <td align="center">58.3</td>
     </tr>
     <tr>
       <td>InternVL2.5-78B</td>
@@ -210,7 +210,7 @@ The model follows a connection pattern of Vision Encoder → MLP Adapter → Lan
     </tr>
     <tr>
       <td>GPQA</td>
-      <td align="center">65.2</td>
       <td align="center">-</td>
       <td align="center">-</td>
       <td align="center">-</td>

     <tr>
       <td>Qwen2.5-72B-Instruct</td>
       <td align="center">❌</td>
+      <td align="center">80.0</td>
       <td align="center">23.3</td>
       <td align="center">49.0</td>
       <td align="center">-</td>
       <td align="center">78.3</td>
       <td align="center">16.0</td>
       <td align="center">65.0</td>
+      <td align="center">65.3</td>
+      <td align="center">66.4</td>
     </tr>
     <tr>
       <td>GPT-4o</td>
       <td align="center">✅</td>
+      <td align="center">74.6</td>
       <td align="center">9.3</td>
+      <td align="center">49.9</td>
       <td align="center">63.8</td>
       <td align="center">69.1</td>
     </tr>
       <td align="center">-</td>
       <td align="center">-</td>
       <td align="center">65.5</td>
+      <td align="center">62.7</td>
     </tr>
     <tr>
       <td>InternVL2.5-78B</td>
     </tr>
     <tr>
       <td>GPQA</td>
+      <td align="center">54.5</td>
       <td align="center">-</td>
       <td align="center">-</td>
       <td align="center">-</td>