Add pipeline tag and paper/project page links
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by nielsr HF Staff - opened
README.md
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license: apache-2.0
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tags:
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---
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# TT-VidT pretrained DiT decoders
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Pretrained DiT decoders for [TT-VidT](https://github.com/KohakuBlueleaf/TTVidT)
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(*Decoupling the Temporal Axis for Efficient Motion-Centric Video Pretraining*,
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NeurIPS 2026).
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these; the training code downloads them automatically through `DECODER_PRETRAINED`,
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e.g. `"KBlueLeaf/TTVidT-decoders/pretrain_video_S_qknorm"`.
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| `pretrain_{imgnet,video}_B_qknorm_nofinal`, `pretrain_{imgnet,video}_L_qknorm` | decoder ablation |
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Recipe: 100k steps (80k for `_80k`), global batch 256, AdamW lr 1e-4. See the
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[code repository](https://github.com/KohakuBlueleaf/TTVidT) for training and usage.
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---
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license: apache-2.0
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tags:
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- video
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- self-supervised-learning
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- diffusion
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pipeline_tag: other
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---
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# TT-VidT pretrained DiT decoders
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Pretrained DiT decoders for [TT-VidT](https://github.com/KohakuBlueleaf/TTVidT)
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(*Decoupling the Temporal Axis for Efficient Motion-Centric Video Pretraining*,
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NeurIPS 2026). [Paper](https://huggingface.co/papers/2609.33419) ·
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[Project page](https://kohakublueleaf.github.io/TTVidT/)
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Each TT-VidT encoder pretraining run initialises its decoder from one of
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these; the training code downloads them automatically through `DECODER_PRETRAINED`,
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e.g. `"KBlueLeaf/TTVidT-decoders/pretrain_video_S_qknorm"`.
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| `pretrain_{imgnet,video}_B_qknorm_nofinal`, `pretrain_{imgnet,video}_L_qknorm` | decoder ablation |
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Recipe: 100k steps (80k for `_80k`), global batch 256, AdamW lr 1e-4. See the
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[code repository](https://github.com/KohakuBlueleaf/TTVidT) for training and usage.
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