Video-Text-to-Text
Transformers
Safetensors
English
qwen2_5_vl
image-text-to-text
text-generation-inference
Instructions to use Video-R1/Video-R1-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Video-R1/Video-R1-7B with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("Video-R1/Video-R1-7B") model = AutoModelForImageTextToText.from_pretrained("Video-R1/Video-R1-7B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b1386d70854cfefd60e569ee033399ce5db5f1e9b001eabb74e0ab417a39a1a9
- Size of remote file:
- 11.4 MB
- SHA256:
- 5eee858c5123a4279c3e1f7b81247343f356ac767940b2692a928ad929543214
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.