モデル情報

MOSS-Image-SFT-DeBand

MATLOWAI · MOSS-Image-SFT-DeBand

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.

翻訳待ちのため原文を表示しています。

画像生成license:apache-2.0
コンテキスト長非公開
入力 → 出力テキスト → 画像
モデルウェイト未確認
情報更新日時2026/11/2 19:15:42
OVERVIEW

モデル紹介

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.

主な特徴

特点摘要待依据来源补齐,不凭模型名称推断能力。

制約と注意点

具体的な制約を判断する出典が不足しています。実際の性能、遅延、データ方針、ライセンス、提供期間を確認してください。

PRICING & COST

出典別料金と費用分析

料金はチャネル・地域・設定によって異なります。各チャネルの料金は個別に表示し、提供元の統一公式料金とは見なしません。

出典・チャネル入力出力課金単位収集日時
確認可能な料金がありません。出典を確認してください。

月額の基本トークン費用を試算

—

試算はキャッシュ割引、段階料金、マルチモーダル追加料金、検索、税金、追加推論出力を含みません。

INDEPENDENT BENCHMARKS

公開評価と実行設定

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。

収録済みの全ランキング →

よくある質問

オープンウェイトなら無料で商用利用できますか?

必ずしもそうではありません。バージョン別のライセンス、商用条件、利用方針を確認してください。自前運用には計算資源と保守費用も必要です。

これはリアルタイムの請求料金ですか?

収集日時付きの料金スナップショットです。最新のバージョン、地域、割引、課金方式は各チャネルで確認してください。

出典と追跡記録

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。