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README.md
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---
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license: apache-2.0
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language:
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- en
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pipeline_tag: image-to-video
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tags:
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- world-model
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- video-generation
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- perspective-switching
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- lora
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- lingbot-world
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base_model: robbyant/lingbot-world-base-cam
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---
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# SwitchWorld FullFlow v2 adapters
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SwitchWorld adds in-stream FP/TP viewpoint switching to LingBot-World. This
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repository contains the completed FullFlow v2 adapter sequence for both the
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high-noise and low-noise branches. The LingBot-World base checkpoint is required
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separately and is not duplicated here.
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## Files
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| File | Role |
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| --- | --- |
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| `front_fp_high_rank128.pt` | high-noise branch after FP expert training |
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| `front_tp_high_rank128.pt` | high-noise branch after TP expert training |
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| `joint_high_rank128.pt` | high-noise final adapter after transition training |
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| `front_fp_low_rank128.pt` | low-noise branch after FP expert training |
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| `front_tp_low_rank128.pt` | low-noise branch after TP expert training |
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| `joint_low_rank128.pt` | low-noise final adapter after transition training |
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For normal inference, use `joint_high_rank128.pt` and
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`joint_low_rank128.pt`. The four intermediate checkpoints are included for
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reproducibility and ablations.
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## Download
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```bash
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hf download PencilHu/SwitchWorld --local-dir checkpoints/switchworld-fullflow-v2
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```
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## Base model and code
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- Base model: [robbyant/lingbot-world-base-cam](https://huggingface.co/robbyant/lingbot-world-base-cam)
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- Code: [yizhiqianbi/SwitchWorld](https://github.com/yizhiqianbi/SwitchWorld)
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- Results: [SwitchWorld Gallery](https://yizhiqianbi.github.io/SwitchWorld-Gallery/archive/)
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## Training layout
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Each noise branch was trained in three ordered stages. The FP expert is updated
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first, the TP expert is updated from that checkpoint, and the transition module
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is updated last while shared/FP/TP weights are frozen. Frozen-component digest
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checks passed for the completed local run.
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## Limitations
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- These are adapters/checkpoints for the SwitchWorld research code, not a
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standalone Diffusers pipeline.
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- Generation inherits the limitations and hardware requirements of
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LingBot-World and Wan2.2.
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- The gallery includes research outputs from multiple stages, including
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baselines and failure cases; it should not be interpreted as a curated quality
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benchmark.
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- Several evaluation metric interfaces in the codebase still have explicitly
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marked mock backends. Do not treat mock values as model claims.
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## License
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Apache-2.0. The required upstream base model and datasets remain subject to
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their own licenses and terms.
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