Video-Text-to-Text
Transformers
Safetensors
English
qwen3_vl
image-text-to-text
video
retrieval
reranking
qwen3-vl
Instructions to use hltcoe/RankVideo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hltcoe/RankVideo with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("hltcoe/RankVideo") model = AutoModelForMultimodalLM.from_pretrained("hltcoe/RankVideo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add GitHub link, paper metadata, and improve model card
Verified signatureHi! I'm Niels, part of the community science team at Hugging Face. This PR improves the model card for **RankVideo** by: - Adding the `arxiv` metadata tag to link the repository to its [research paper](https://huggingface.co/papers/2602.02444). - Adding `library_name: transformers` to the metadata based on the `config.json` architecture. - Adding a link to the official [GitHub repository](https://github.com/tskow99/RANKVIDEO-Reasoning-Reranker). - Fixing the formatting of the usage example and the BibTeX block. These changes make the model more discoverable and provide better context for users.ed8a342
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