How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Ricky06662/TaskRouter-1.5B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Ricky06662/TaskRouter-1.5B",
		"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/Ricky06662/TaskRouter-1.5B
Quick Links

VisionReasoner: Unified Visual Perception and Reasoning via Reinforcement Learning

This repository contains the code for the model described in the paper VisionReasoner: Unified Visual Perception and Reasoning via Reinforcement Learning.

Code: https://github.com/dvlab-research/VisionReasoner

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