Image-Text-to-Text
Transformers
Safetensors
qwen2_vl
conversational
text-generation-inference
How to use from
vLLM
# Gated model: Login with a HF token with gated access permission
hf auth login
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "CraftJarvis/minecraft-textvla-qwen2vl-7b-2509"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "CraftJarvis/minecraft-textvla-qwen2vl-7b-2509",
		"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/CraftJarvis/minecraft-textvla-qwen2vl-7b-2509
Quick Links

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Minecraft-Textvla-Qwen2vl-7b-2509

💻 Usage

You can download and use this model with:

python examples/rollout_openha.py \
    --output_mode text_action  \
    --vlm_client_mode hf \
    --system_message_tag text_action \
    --model_ips localhost --model_ports 11000 \
    --model_path CraftJarvis/minecraft-textvla-qwen2vl-7b-2509 \
    --model_id minecraft-textvla-qwen2vl-7b-2509 \
    --record_path "~/evaluate" \
    --max_steps_num 200 \
    --num_rollouts 8
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Model size
8B params
Tensor type
F16
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