Video-Text-to-Text
Transformers
Safetensors
English
qwen2_5_vl
image-text-to-text
multimodal
text-generation-inference
Instructions to use OpenGVLab/VideoChat-R1-thinking_7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/VideoChat-R1-thinking_7B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("OpenGVLab/VideoChat-R1-thinking_7B") model = AutoModelForMultimodalLM.from_pretrained("OpenGVLab/VideoChat-R1-thinking_7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from OpenGVLab/VideoChat-R1-thinking_7B: direct link, hf CLI and curl.
- Browser
- Download file 8.25 kB
-
https://huggingface.co/OpenGVLab/VideoChat-R1-thinking_7B/resolve/main/training_args.bin
- Command line
-
hf download hf://OpenGVLab/VideoChat-R1-thinking_7B/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/OpenGVLab/VideoChat-R1-thinking_7B/resolve/main/training_args.bin
8.25 kB
- Xet hash:
- d52163e77a6c9eb1c3c9a6edb91365757f7b31a469400bc974ac0af89ae3f602
- Size of remote file:
- 8.25 kB
- SHA256:
- b8ac41a0ee0d9488a70f8d39213ee0d1a518a082d8c2ff7250202bb7be791efd
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