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
Add video-text-to-text pipeline tag, link to paper, project page, and code
#1
by nielsr HF Staff - opened
This PR improves the model card for VideoSearch-R1 DiDeMo Stage 2 by:
- Adding the
pipeline_tag: video-text-to-textmetadata to ensure it is discoverable under the correct category on the Hub. - Linking the model card to its research paper: VideoSearch-R1: Iterative Video Retrieval and Reasoning via Soft Query Refinement.
- Adding links to the official project page and GitHub repository.
- Adding the BibTeX citation block.
happy8825 changed pull request status to merged