Video-Text-to-Text
Transformers
Safetensors
English
qwen2_5_vl
image-text-to-text
text-generation-inference
Instructions to use Video-R1/Qwen2.5-VL-7B-COT-SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Video-R1/Qwen2.5-VL-7B-COT-SFT with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Video-R1/Qwen2.5-VL-7B-COT-SFT") model = AutoModelForMultimodalLM.from_pretrained("Video-R1/Qwen2.5-VL-7B-COT-SFT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
Verified signaturef71f0f1 -
Improve model card: Add pipeline tag, library name, paper link, authors, and sample usage (#2)
Verified signature- Improve model card: Add pipeline tag, library name, paper link, authors, and sample usage (b73f590a320a995a11c273ed11efb05b6e423486) Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>cb9777b
-
Initial model upload
Verified signature0c82cb6 -
Update README.md
Verified signatureeef2c81 -
Update README.md
Verified signature2ec4578 -
Update README.md
Verified signature39334b7 -
Update README.md
Verified signatureThe SFT cold start models trained by Video-R1-COT-165k dataset. Please refer to 'Video-R1: Reinforcing Video Reasoning in MLLMs' for details Code: https://github.com/tulerfeng/Video-R135b371b -
initial commit
Verified signature0109fc6