Video-Text-to-Text
Transformers
Safetensors
qwen3_vl
image-text-to-text
video-retrieval
temporal-grounding
videosearch-r1
Instructions to use VideoSearchR1/didemo-stage2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VideoSearchR1/didemo-stage2 with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("VideoSearchR1/didemo-stage2") model = AutoModelForMultimodalLM.from_pretrained("VideoSearchR1/didemo-stage2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81ba189117386911cebccbc60d7c4ebc2634f47402d8b1d85d98b3ac6d2032b2
- Size of remote file:
- 11.4 MB
- SHA256:
- eda24b2b728f3383edd5ac02192ea21c77b021c338367b1542fa2cbe4c0f6d44
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