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