MOSS-Image-SFT-DeBand

Model overview

The MOSS-Image **SFT** model often draws faint, evenly spaced **vertical color stripes** across smooth areas like skies, fog, backdrops and walls. This repo has two **banding-fix LoRAs** that remove them while keeping the image close to what SFT would have made, plus **preset workflows** that pair the fix with community speed LoRAs for 10–14 step (or 4–8 step) generation. > **Update, October 2026.** Since this repo went up, nynxz's Destripe LoRA (built on this investigation) has become the gentlest fix: it reduces the stripes while keeping images almost exactly as SFT made them. This update adds **DeBand Strong** (experimental: the strongest cleanup short of Base, with more drift), an **interactive comparison of every fix** (https://matlowai.github.io/MOSS-DeBand/, also in `web/` to run locally), the **full research write-up** (RESEARCH.md) including what didn't work, and the **measurement tools** (`research/`). Quick guide: minimal change → nynxz Destripe; cleanest flat backgrounds → DeBand Strong; one-file int8 → the int8 repo below. **Just want one file that works?** MOSS-Image-SFT-DeBand-int8 has the fix (and the Fast preset) merged into ready-to-run 5.4 GB int8 models. No LoRAs or custom nodes.

Key features

特点摘要待依据来源补齐，不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

Source prices & cost analysis

Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.

Public benchmarks & run configuration

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

Frequently asked questions

Sources & traceability

许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。