Add transformers library tag and model description (#1)
Browse files- Add transformers library tag and model description (3dc426bcc197589b4becd3377f54316188fc9a20)
Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>
README.md
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pipeline_tag: video-text-to-text
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# EVA: Efficient Reinforcement Learning for End-to-End Video Agent
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[](https://arxiv.org/abs/2603.22918)
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[](https://github.com/wangruohui/EfficientVideoAgent)
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[](https://huggingface.co/WRHC/EfficientVideoAgent/)
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This repository contains the official evaluation code for the model proposed in
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pipeline_tag: video-text-to-text
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library_name: transformers
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# EVA: Efficient Reinforcement Learning for End-to-End Video Agent
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[](https://arxiv.org/abs/2603.22918)
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[](https://github.com/wangruohui/EfficientVideoAgent)
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[](https://huggingface.co/WRHC/EfficientVideoAgent/)
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This repository contains the official evaluation code for the model proposed in the paper [EVA: Efficient Reinforcement Learning for End-to-End Video Agent](https://arxiv.org/abs/2603.22918).
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EVA (Efficient Video Agent) is an end-to-end framework that enables "planning-before-perception" through iterative summary-plan-action-reflection reasoning. Unlike passive recognizers, EVA autonomously decides what to watch, when to watch, and how to watch, achieving query-driven and efficient video understanding.
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