Video-Text-to-Text
Transformers
Safetensors
English
qwen2_5_vl
image-text-to-text
multimodal
text-generation-inference
Instructions to use OpenGVLab/VideoChat-R1_7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/VideoChat-R1_7B with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("OpenGVLab/VideoChat-R1_7B") model = AutoModelForImageTextToText.from_pretrained("OpenGVLab/VideoChat-R1_7B") - Notebooks
- Google Colab
- Kaggle
VideoChat-R1_7B / runs /Mar31_23-18-18_SH-IDC1-10-140-37-61 /events.out.tfevents.1743434449.SH-IDC1-10-140-37-61
- Xet hash:
- 1caadbc4365cee86ff9696f498728ca1ee7a1ff8b85407d640dd75a9d6abdd0f
- Size of remote file:
- 6.97 kB
- SHA256:
- af850a62237e03633233d6db19141233644c439a1374c1593923e08a11a4053d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.