Update Deploy - now use fetch weight

DEPLOY.md

@@ -77,7 +77,17 @@ Three models are used by default: `hustvl/vitmatte-base-composition-1k` (matting
 `ZhengPeng7/BiRefNet` (default segmenter), `skytnt/anime-seg` (optional segmenter).
 A fourth model, `ZhengPeng7/BiRefNet_HR-matting` (~425 MB), is only needed if you
 enable the **cross-check** veto — see the note at the end of this section.
-Pick **one** of the two layouts below.
+
+**Quick path (recommended):** run the bundled script — no arguments — to download
+every model into `models/` via the hf-mirror (proxy bypassed, Xet disabled,
+already-present folders skipped). Afterwards the app has full functionality offline:
+
+```bash
+python scripts/fetch_weights.py
+```
+
+The two manual layouts below are for finer control (e.g. a shared HF cache, or
+picking specific models).
 
 ### Option A — HuggingFace cache + offline mode (recommended)
 

DEPLOY_ZH.md

@@ -71,7 +71,16 @@ print('torch', torch.__version__, 'cuda=', torch.version.cuda)"
 默认用到三个模型：`hustvl/vitmatte-base-composition-1k`（抠图）、
 `ZhengPeng7/BiRefNet`（默认分割）、`skytnt/anime-seg`（可选分割）。
 第四个模型 `ZhengPeng7/BiRefNet_HR-matting`（约 425 MB）只有在启用 **cross-check（交叉校验）
-否决**时才需要——见本节末尾说明。下面两种放法**二选一**。
+否决**时才需要——见本节末尾说明。
+
+**一键方式（推荐）**：跑仓库自带脚本（无参数），经 hf-mirror 把所有模型下到 `models/`
+（绕过代理、禁用 Xet、已存在的文件夹自动跳过）。跑完主 app 即离线全功能可用：
+
+```bash
+python scripts/fetch_weights.py
+```
+
+下面两种手动放法用于更精细的控制（比如共享 HF 缓存、只下部分模型），**二选一**。
 
 ### 方案 A —— HuggingFace 缓存 + 离线模式（推荐）