Video-Text-to-Text
Transformers
Safetensors
qwen3_vl
image-text-to-text
video-retrieval
temporal-grounding
videosearch-r1
Instructions to use VideoSearchR1/activitynet-stage1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VideoSearchR1/activitynet-stage1 with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("VideoSearchR1/activitynet-stage1") model = AutoModelForMultimodalLM.from_pretrained("VideoSearchR1/activitynet-stage1") - Notebooks
- Google Colab
- Kaggle
Add pipeline tag and links to paper, code, and project page
#1
by nielsr HF Staff - opened
This PR improves the model card by:
- Adding the
pipeline_tag: video-text-to-textmetadata to make the model discoverable in the Hugging Face Hub under the correct task. - Linking the model card to the official paper VideoSearch-R1: Iterative Video Retrieval and Reasoning via Soft Query Refinement.
- Adding direct links to the official project page and the GitHub codebase repository.
- Adding the BibTeX citation from the paper.
happy8825 changed pull request status to merged