<p>The Ling-mini-2.0 text encoders that the Ming-Image-0.1-Design models run on, hosted separately so any Ming Image checkpoint - ours or a community finetune - can point at them instead of shipping its own copy.</p>

<p><strong>Originally released by <a target="_blank" rel="ugc" href="https://huggingface.co/inclusionAI">inclusionAI</a> on Hugging Face under the MIT license</strong>, and repackaged as single files for ComfyUI by <a target="_blank" rel="ugc" href="https://huggingface.co/Comfy-Org/Ming-Image">Comfy-Org</a>. All credit for the weights goes to the inclusionAI team.</p>

<h3><strong>Two versions, and they are not interchangeable</strong></h3>
<p>The base checkpoint and the layer-decomposition checkpoint use different encoder weights. Pick the version that matches the model you are running:</p>
<ul>
<li><strong>Design</strong> - for <a target="_blank" rel="ugc" href="https://civarchive.com/models/2961930">Ming Image Design</a> and anything finetuned from it. Available in BF16, int8 and w4a8.</li>
<li><strong>Layer</strong> - for <a target="_blank" rel="ugc" href="https://civarchive.com/models/2962010">Ming Image Design Layer</a>. Available in BF16 and int8.</li>
</ul>
<p>Loading the wrong one does not error cleanly; it produces noise. If you are unsure which you have, match the filename - the Layer weights carry <code>layer</code> in the name.</p>

<h3><strong>Pick one file, not all of them</strong></h3>
<p>Each file is the whole encoder at a different precision, so you need exactly one. BF16 is the reference weights at full size. int8 is the practical default for most setups. w4a8 (Design only) is the smallest and the one to reach for on limited VRAM. Every file is marked optional for that reason - nothing here requires anything else here.</p>

<h3><strong>Where these go</strong></h3>
<p>In ComfyUI, <code>models/text_encoders/</code>. This is a component rather than a runnable model, so there is no Generate button and no on-site generation - if you want to generate with Ming, that is the <a target="_blank" rel="ugc" href="https://civarchive.com/models/2961930">Ming Image Design</a> page, where the encoder is already handled for you.</p>

<h3><strong>Links</strong></h3>
<ul>
<li><strong>Source:</strong> <a target="_blank" rel="ugc" href="https://huggingface.co/inclusionAI/Ming-Image-0.1-Design">Ming-Image-0.1-Design</a> and <a target="_blank" rel="ugc" href="https://huggingface.co/inclusionAI/Ming-Image-0.1-Design-Layer">Ming-Image-0.1-Design-Layer</a></li>
<li><strong>Repackaged files:</strong> <a target="_blank" rel="ugc" href="https://huggingface.co/Comfy-Org/Ming-Image">Comfy-Org/Ming-Image</a></li>
<li><strong>Code:</strong> <a target="_blank" rel="ugc" href="https://github.com/inclusionAI/Ming-Image">github.com/inclusionAI/Ming-Image</a></li>
</ul>

Ming Image Text Encoders

mingImageText_layer_bf16.safetensors

mingImageText_layer_int8.safetensors

Layer

Design

<p>Ming-Image-0.1-Design-Layer takes a finished, flattened design and pulls it back apart into separate transparent layers. Give it an image and a layer plan and it returns the requested number of RGBA layers - background, shapes, text - each one editable on its own. It is the companion to Ming-Image-0.1-Design, and a different checkpoint with a different job.</p>

<p><strong>Originally released by <a target="_blank" rel="ugc" href="https://huggingface.co/inclusionAI/Ming-Image-0.1-Design-Layer">inclusionAI</a> on Hugging Face under the MIT license.</strong> All credit for the model goes to the inclusionAI team. Civitai is hosting a mirror so the weights are easy to get hold of - please head to the original repository for updates and to follow the project directly.</p>

<h3><strong>Download only - this one does not run on-site</strong></h3>
<p>Layer decomposition is not a workflow the Civitai generator offers, so there is no Generate button here. The files below are for running it yourself, in ComfyUI or with inclusionAI's own inference code. If you want to generate Ming designs on-site, that is the <a target="_blank" rel="ugc" href="https://civarchive.com/models/2961930">Ming Image Design</a> model.</p>

<h3><strong>Built by</strong></h3>
<ul>
<li><a target="_blank" rel="ugc" href="https://huggingface.co/inclusionAI">inclusionAI</a> - the Ming-Image series and the Ling-mini-2.0 text encoder it runs on</li>
<li><a target="_blank" rel="ugc" href="https://github.com/inclusionAI/Ming-Image">The Ming-Image repository</a> - reference inference code and the layer-decomposition demo</li>
<li><a target="_blank" rel="ugc" href="https://huggingface.co/Comfy-Org/Ming-Image">Comfy-Org</a> - the repackaged single-file weights this mirror is built from</li>
</ul>

<h3><strong>What it produces</strong></h3>
<p>One input image plus a prompt describing the layer plan, and you get back that many RGBA layers with real alpha. The released card-making example splits a greetings card into six. Layer count follows the plan you give it rather than being fixed, and the output keeps the reference image's aspect ratio.</p>

<h3><strong>Recommended settings</strong></h3>
<ul>
<li><strong>Resolution:</strong> 1024 for quality, 512 for speed. Unlike text-to-image, output is not square - the working size is picked from the selected bucket and the reference ratio is preserved.</li>
<li><strong>Steps:</strong> 12.</li>
<li><strong>CFG scale:</strong> 2.0. Note this differs from Design, which wants 1.0.</li>
<li><strong>Precision:</strong> BF16.</li>
</ul>

<h3><strong>Files here</strong></h3>
<p>The Comfy-Org repackaging of both halves of the Layer checkpoint: the diffusion model in BF16 and an int8 quantization, and its own Ling-mini-2.0 text encoder in BF16 and int8. The text encoders are specific to Layer and are not interchangeable with the ones on the Design model.</p>

<h3><strong>Links</strong></h3>
<ul>
<li><strong>Source:</strong> <a target="_blank" rel="ugc" href="https://huggingface.co/inclusionAI/Ming-Image-0.1-Design-Layer">inclusionAI/Ming-Image-0.1-Design-Layer</a> on Hugging Face</li>
<li><strong>Code:</strong> <a target="_blank" rel="ugc" href="https://github.com/inclusionAI/Ming-Image">github.com/inclusionAI/Ming-Image</a></li>
<li><strong>ModelScope:</strong> <a target="_blank" rel="ugc" href="https://www.modelscope.cn/models/inclusionAI/Ming-Image-0.1-Design-Layer">inclusionAI/Ming-Image-0.1-Design-Layer</a></li>
<li><strong>Demo:</strong> <a target="_blank" rel="ugc" href="https://huggingface.co/spaces/Xiaolong-Wang/Ming-Image-0.1-Design-Layer">Hugging Face Space</a></li>
<li><strong>Agent skills:</strong> <a target="_blank" rel="ugc" href="https://github.com/inclusionAI/ling-cookbook/tree/main/resources/recommended-skills/ling-ui-design">Ling UI Design</a> and <a target="_blank" rel="ugc" href="https://github.com/inclusionAI/ling-cookbook/tree/main/resources/recommended-skills/image-to-editable-ppt">Image to Editable PPT</a></li>
</ul>

Files with SHA256: 086324b766a04844dc918866e48e40b5cede499d869ac3fa05ceaa87ad7c6850