[English] This is a quantized GGUF version of the NSFW-Wan-UMT5-XXL text encoder. It is designed to be used with the Wan 2.1 video generation model in ComfyUI. File Guide :<ul><li>Pruned Model fp16 (3.4GB) = Q4_K_M (Recommended for 12GB VRAM)</li><li>Pruned Model bf16 (3.8GB) = Q5_K_M (Higher Quality)</li></ul>Why use this?<ul><li>Uncensored: Fixes the issue where the official Wan 2.1 model refuses to generate NSFW or specific prompts (it plays dumb).</li><li>Lightweight: GGUF format allows you to run this huge T5 encoder with much less VRAM (Q4/Q5 versions).</li></ul>How to use:<ol><li>Place the <code>.gguf</code> file in your <code>ComfyUI/models/text_encoders/</code> folder.</li><li>Load it using the CLIPLoader (GGUF) node.</li><li>Set the type to <code>wan</code>.</li></ol>Credits &amp; Disclaimer:<ul><li>Original Weights: <a target="_blank" rel="ugc" href="https://huggingface.co/NSFW-API/NSFW-Wan-UMT5-XXL">NSFW-API/NSFW-Wan-UMT5-XXL</a> on HuggingFace.</li><li>Conversion: Quantized by MomusAki.</li><li>If the original author (NSFW-API) has any objections to this quantization release, please contact me and I will take it down immediately.</li></ul><hr />[中文] 这是 NSFW-Wan-UMT5-XXL 文本编码器的 GGUF 量化版本。 专为 ComfyUI 中的 Wan 2.1 视频生成模型打造。文件说明:<ul><li>Pruned Model fp16 (3.4GB) = Q4_K_M (Recommended for 12GB VRAM)</li><li>Pruned Model bf16 (3.8GB) = Q5_K_M (Higher Quality)</li></ul>主要作用：<ul><li>解除限制： 完美解决了 Wan 2.1 官方模型对 NSFW 或特定敏感提示词“装傻”、“听不懂”的问题。</li><li>节省显存： 相比原始的 safetensors 格式，GGUF 版本（Q4/Q5）大幅降低了显存占用，让 12G/16G 显卡也能流畅运行。</li></ul>使用方法：<ol><li>将 <code>.gguf</code> 文件放入 <code>ComfyUI/models/text_encoders/</code> 文件夹。</li><li>在 ComfyUI 中使用 CLIPLoader (GGUF) 节点加载。</li><li>Type 选项选择 <code>wan</code>。</li></ol>致谢与声明：<ul><li>原始权重： 源自 HuggingFace 上的 <a target="_blank" rel="ugc" href="https://huggingface.co/NSFW-API/NSFW-Wan-UMT5-XXL">NSFW-API/NSFW-Wan-UMT5-XXL</a>。</li><li>量化制作： 由 MomusAki 转换。</li><li>本模型仅为方便社区使用的量化版本。如果原作者 (NSFW-API) 认为此发布不妥，请联系我，我会立即下架。</li></ul><ul><li>Workflow：<a target="_blank" rel="ugc" href="https://civarchive.com/models/2417743?modelVersionId=2718266">https://civarchive.com/models/2417743?modelVersionId=2718266</a></li></ul>

Files with SHA256: 1e1ed5c5ddbdcd9d6a1e067d29925ce205008a1e069370735783c5e701004054