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+}

klein-9b/lora/MCSC - Minecraft Skin Creator/extra_data-vid_2828017/model_dict-mid_2504687-vid_2828017.json

@@ -0,0 +1,550 @@
+{
+  "id": 2504687,
+  "name": "MCSC - Minecraft Skin Creator",
+  "description": "<p>🌌 <strong>Overview</strong><br /><em>This LoRA is designed to generate high-quality Minecraft skins with exceptional accuracy, converting characters or people into clean and usable 64×64 texture maps.</em><br /></p><p>🧩 <strong>Recommended Settings</strong></p><ul><li><p><strong>Trigger word:</strong> <code>MCSC:</code></p></li><li><p><strong>Strength:</strong> <code>1.2 – 1.5</code></p></li><li><p><strong>Resolution:</strong> <code>512x512</code></p></li><li><p><strong>Samplers:</strong> <code>Euler Ancestral</code>, <code>ICM</code>, <code>er_sde</code>, <code>sa_solver</code></p></li></ul><hr /><p>💡 <strong>Pro Tip</strong></p><p>Use this prompt for best results:<strong><em><br />V1:</em></strong></p><pre><code>MCSC: transform this person into a 64x64 pixel texture for a minecraft texture.</code></pre><p><strong><em>V2 &amp; V3:</em></strong></p><pre><code>MCSC: transform this person into a 64x64 Minecraft skin texture with aligned UV layout, strict pixel grid, hard edges, consistent and coherent pixel placement across all body parts.</code></pre><p><strong><em>Txt2Img:</em></strong></p><pre><code>MCSC: 64x64 Minecraft skin texture with aligned UV layout, strict pixel grid, hard edges, consistent and coherent pixel placement across all body parts, &lt;prompt here&gt;</code></pre><hr /><p>📝 <strong>V3 &amp; Text-to-Image Notes</strong></p><p><em>At this stage, the model is considered close to its practical limit. Further improvements would likely result in diminishing returns, making </em><strong><em>Version 3 the final release of this LoRA.</em></strong><em><br /></em></p><p><em>A</em><strong><em> Text-to-Image variant</em></strong><em> is included, allowing direct generation of Minecraft skins without requiring a reference image.</em><br /></p><p><em>Consistency in V3 is improved over both V1 and V2. Detail levels are more balanced — generally higher than V2, though occasionally slightly below V1. This reflects an inherent trade-off between detail and consistency.</em><br /></p><p><em>All evaluations and showcase results were produced under a controlled baseline using consistent prompts, resolution, and generation settings. Variations outside this setup were not extensively tested, as the model was designed around this workflow.<br /></em></p><p><em>Users are </em><strong><em>encouraged to experiment beyond this baseline</em></strong><em> — including prompt variation, resolution changes, higher-resolution inputs, and multi-pass workflows (such as second-pass refinement). </em><strong><em>Alternative pipelines may produce results that surpass the provided showcase</em></strong><em>, which is intentionally representative rather than optimized.<br /></em></p><p><span style=\"color:rgb(64, 192, 87)\"><strong><em>Feedback and community interaction are welcome. Suggestions, ideas, and new concepts are encouraged via Discord or community channels.</em></strong></span><br /></p><p><span style=\"color:rgb(250, 176, 5)\"><strong><em>This marks the conclusion of development for this LoRA. Future releases — including new models, concepts, and utility-focused tools — are planned.</em></strong></span></p><hr /><p><strong><em>⚠️ Known Limitations &amp; Recommendations</em></strong></p><ul><li><p><em>The recommended strength range for all loras is </em><strong><em>1.1 to 1.5</em></strong><em>. Values outside this range may degrade quality.</em><br /></p></li><li><p><em>A latent resolution of </em><strong><em>512×512 is required</em></strong><em> for optimal performance.</em><br /></p></li><li><p><strong><em>Generation quality can vary significantly between seeds. Some seeds may produce near-perfect outputs, while others can result in visible artifact</em></strong><em>s such as pixel inconsistencies, misalignment, or structural errors.</em><br /></p></li><li><p><strong><em>Higher-quality, cleaner, and more consistent inputs tend to produce significantly better and more stable results</em></strong><em>, while low-quality inputs may lead to noisier or less accurate skins.</em><br /></p></li><li><p><em>The model was trained exclusively on full-body images. Inputs that do not follow this format may lead to inconsistent or unintended results.</em><br /></p></li><li><p><em>Inputs with </em><strong><em>excessive detail or visual complexity may not translate well into the 64×64 format.</em></strong><br /></p></li><li><p><em>Scenes that are not clean — such as images with multiple characters, background activity, or interactions with the main subject — often lead to degraded quality and structural distortions. For best results, use a single, clearly isolated character.</em><br /></p></li><li><p><em>Characters holding objects (such as weapons or accessories)</em><strong><em> may cause distortions in the generated skin,</em></strong><em> as the model does not reliably distinguish between the character and attached elements. It is recommended to remove any items such as weapons, hats, bandanas, or accessories that should not appear in the final texture.</em><br /></p></li><li><p><em>Due to the training being based primarily on front-facing full-body images, </em><strong><em>the back side of the character is inferred by the model rather than learned directly.</em></strong><em> In practice, this often results in a mirrored or approximate reconstruction of the front, which is inherently prone to errors.</em></p></li></ul><p><em>For best results, it </em><strong><em>is strongly recommended to generate multiple seeds and select the best outcome</em></strong><em>. </em><strong><em>For professional use, additional manual refinement is advised</em></strong><em> — editing and correcting the generated skin to ensure full accuracy.</em><br /></p><p><em>In most cases,</em><strong><em> the model completes the majority of the work, with only final adjustments required</em></strong><em>. Occasionally, a near-perfect result may be obtained directly depending on the seed, but this should be considered situational rather than consistent behavior.</em></p><hr /><p>🧑‍🎮 <strong>How to Use a Generated Skin in Minecraft</strong></p><p>After generating your image, you will notice a purple mask covering the texture. This mask must be removed before use.</p><p>Use the script <code>convertToOriginal.py</code> to:</p><ul><li><p>Remove the purple mask</p></li><li><p>Convert the image to the correct <strong>64×64 Minecraft format</strong></p></li></ul><p>📥 <strong>Download Script:</strong><br /><a target=\"_blank\" rel=\"ugc\" href=\"https://drive.google.com/file/d/1wlEAAOvfg_OJR-ctAyEPsg7OiV5IKE5h/view?usp=sharing\">https://drive.google.com/file/d/1wlEAAOvfg_OJR-ctAyEPsg7OiV5IKE5h/view?usp=sharing</a></p><p>👀 <strong>Preview Your Skin:</strong><br /><a target=\"_blank\" rel=\"ugc\" href=\"https://customuse.com/free-tools/minecraft-clothes-preview?_x_tr_hist=true\">https://customuse.com/free-tools/minecraft-clothes-preview?_x_tr_hist=true</a></p><hr /><p>⚙️ <strong>How to Install &amp; Run the Script</strong></p><ul><li><p>Install Python (if not already installed)</p></li><li><p>Install the required library:</p></li></ul><pre><code>pip install pillow numpy</code></pre><ul><li><p>Place your generated image in the same folder as the script</p></li><li><p>Run:</p></li></ul><pre><code>python convertToOriginal.py ./</code></pre><ul><li><p>The script will generate a clean <strong>64×64 skin ready for Minecraft</strong></p></li></ul><hr /><p>👤 <strong>Contact &amp; Support</strong></p><p>💬 Discord: <strong>hex_wave</strong><br />💖 Brazilian Discord server: <a target=\"_blank\" rel=\"ugc\" href=\"https://discord.gg/kMWpCwUCYw\">https://discord.gg/kMWpCwUCYw</a></p><p>If you enjoy this work, consider supporting:<br />☕ <a target=\"_blank\" rel=\"ugc\" href=\"https://ko-fi.com/retrowavex32\">https://ko-fi.com/retrowavex32</a></p>",
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+    "models": [
+      "flux-2-klein-9b-fp8.safetensors"
+    ],
+    "sampler": "Euler a"
+  },
+  "availability": "Public",
+  "hasMeta": true,
+  "hasPositivePrompt": false,
+  "onSite": false,
+  "remixOfId": null
+}

klein-9b/lora/MCSC - Minecraft Skin Creator/extra_data-vid_2828040/model_dict-mid_2504687-vid_2828040.json

@@ -0,0 +1,550 @@
+{
+  "id": 2504687,
+  "name": "MCSC - Minecraft Skin Creator",
+  "description": "<p>🌌 <strong>Overview</strong><br /><em>This LoRA is designed to generate high-quality Minecraft skins with exceptional accuracy, converting characters or people into clean and usable 64×64 texture maps.</em><br /></p><p>🧩 <strong>Recommended Settings</strong></p><ul><li><p><strong>Trigger word:</strong> <code>MCSC:</code></p></li><li><p><strong>Strength:</strong> <code>1.2 – 1.5</code></p></li><li><p><strong>Resolution:</strong> <code>512x512</code></p></li><li><p><strong>Samplers:</strong> <code>Euler Ancestral</code>, <code>ICM</code>, <code>er_sde</code>, <code>sa_solver</code></p></li></ul><hr /><p>💡 <strong>Pro Tip</strong></p><p>Use this prompt for best results:<strong><em><br />V1:</em></strong></p><pre><code>MCSC: transform this person into a 64x64 pixel texture for a minecraft texture.</code></pre><p><strong><em>V2 &amp; V3:</em></strong></p><pre><code>MCSC: transform this person into a 64x64 Minecraft skin texture with aligned UV layout, strict pixel grid, hard edges, consistent and coherent pixel placement across all body parts.</code></pre><p><strong><em>Txt2Img:</em></strong></p><pre><code>MCSC: 64x64 Minecraft skin texture with aligned UV layout, strict pixel grid, hard edges, consistent and coherent pixel placement across all body parts, &lt;prompt here&gt;</code></pre><hr /><p>📝 <strong>V3 &amp; Text-to-Image Notes</strong></p><p><em>At this stage, the model is considered close to its practical limit. Further improvements would likely result in diminishing returns, making </em><strong><em>Version 3 the final release of this LoRA.</em></strong><em><br /></em></p><p><em>A</em><strong><em> Text-to-Image variant</em></strong><em> is included, allowing direct generation of Minecraft skins without requiring a reference image.</em><br /></p><p><em>Consistency in V3 is improved over both V1 and V2. Detail levels are more balanced — generally higher than V2, though occasionally slightly below V1. This reflects an inherent trade-off between detail and consistency.</em><br /></p><p><em>All evaluations and showcase results were produced under a controlled baseline using consistent prompts, resolution, and generation settings. Variations outside this setup were not extensively tested, as the model was designed around this workflow.<br /></em></p><p><em>Users are </em><strong><em>encouraged to experiment beyond this baseline</em></strong><em> — including prompt variation, resolution changes, higher-resolution inputs, and multi-pass workflows (such as second-pass refinement). </em><strong><em>Alternative pipelines may produce results that surpass the provided showcase</em></strong><em>, which is intentionally representative rather than optimized.<br /></em></p><p><span style=\"color:rgb(64, 192, 87)\"><strong><em>Feedback and community interaction are welcome. Suggestions, ideas, and new concepts are encouraged via Discord or community channels.</em></strong></span><br /></p><p><span style=\"color:rgb(250, 176, 5)\"><strong><em>This marks the conclusion of development for this LoRA. Future releases — including new models, concepts, and utility-focused tools — are planned.</em></strong></span></p><hr /><p><strong><em>⚠️ Known Limitations &amp; Recommendations</em></strong></p><ul><li><p><em>The recommended strength range for all loras is </em><strong><em>1.1 to 1.5</em></strong><em>. Values outside this range may degrade quality.</em><br /></p></li><li><p><em>A latent resolution of </em><strong><em>512×512 is required</em></strong><em> for optimal performance.</em><br /></p></li><li><p><strong><em>Generation quality can vary significantly between seeds. Some seeds may produce near-perfect outputs, while others can result in visible artifact</em></strong><em>s such as pixel inconsistencies, misalignment, or structural errors.</em><br /></p></li><li><p><strong><em>Higher-quality, cleaner, and more consistent inputs tend to produce significantly better and more stable results</em></strong><em>, while low-quality inputs may lead to noisier or less accurate skins.</em><br /></p></li><li><p><em>The model was trained exclusively on full-body images. Inputs that do not follow this format may lead to inconsistent or unintended results.</em><br /></p></li><li><p><em>Inputs with </em><strong><em>excessive detail or visual complexity may not translate well into the 64×64 format.</em></strong><br /></p></li><li><p><em>Scenes that are not clean — such as images with multiple characters, background activity, or interactions with the main subject — often lead to degraded quality and structural distortions. For best results, use a single, clearly isolated character.</em><br /></p></li><li><p><em>Characters holding objects (such as weapons or accessories)</em><strong><em> may cause distortions in the generated skin,</em></strong><em> as the model does not reliably distinguish between the character and attached elements. It is recommended to remove any items such as weapons, hats, bandanas, or accessories that should not appear in the final texture.</em><br /></p></li><li><p><em>Due to the training being based primarily on front-facing full-body images, </em><strong><em>the back side of the character is inferred by the model rather than learned directly.</em></strong><em> In practice, this often results in a mirrored or approximate reconstruction of the front, which is inherently prone to errors.</em></p></li></ul><p><em>For best results, it </em><strong><em>is strongly recommended to generate multiple seeds and select the best outcome</em></strong><em>. </em><strong><em>For professional use, additional manual refinement is advised</em></strong><em> — editing and correcting the generated skin to ensure full accuracy.</em><br /></p><p><em>In most cases,</em><strong><em> the model completes the majority of the work, with only final adjustments required</em></strong><em>. Occasionally, a near-perfect result may be obtained directly depending on the seed, but this should be considered situational rather than consistent behavior.</em></p><hr /><p>🧑‍🎮 <strong>How to Use a Generated Skin in Minecraft</strong></p><p>After generating your image, you will notice a purple mask covering the texture. This mask must be removed before use.</p><p>Use the script <code>convertToOriginal.py</code> to:</p><ul><li><p>Remove the purple mask</p></li><li><p>Convert the image to the correct <strong>64×64 Minecraft format</strong></p></li></ul><p>📥 <strong>Download Script:</strong><br /><a target=\"_blank\" rel=\"ugc\" href=\"https://drive.google.com/file/d/1wlEAAOvfg_OJR-ctAyEPsg7OiV5IKE5h/view?usp=sharing\">https://drive.google.com/file/d/1wlEAAOvfg_OJR-ctAyEPsg7OiV5IKE5h/view?usp=sharing</a></p><p>👀 <strong>Preview Your Skin:</strong><br /><a target=\"_blank\" rel=\"ugc\" href=\"https://customuse.com/free-tools/minecraft-clothes-preview?_x_tr_hist=true\">https://customuse.com/free-tools/minecraft-clothes-preview?_x_tr_hist=true</a></p><hr /><p>⚙️ <strong>How to Install &amp; Run the Script</strong></p><ul><li><p>Install Python (if not already installed)</p></li><li><p>Install the required library:</p></li></ul><pre><code>pip install pillow numpy</code></pre><ul><li><p>Place your generated image in the same folder as the script</p></li><li><p>Run:</p></li></ul><pre><code>python convertToOriginal.py ./</code></pre><ul><li><p>The script will generate a clean <strong>64×64 skin ready for Minecraft</strong></p></li></ul><hr /><p>👤 <strong>Contact &amp; Support</strong></p><p>💬 Discord: <strong>hex_wave</strong><br />💖 Brazilian Discord server: <a target=\"_blank\" rel=\"ugc\" href=\"https://discord.gg/kMWpCwUCYw\">https://discord.gg/kMWpCwUCYw</a></p><p>If you enjoy this work, consider supporting:<br />☕ <a target=\"_blank\" rel=\"ugc\" href=\"https://ko-fi.com/retrowavex32\">https://ko-fi.com/retrowavex32</a></p>",
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klein-9b/lora/Transparent Clothes (Klein 9b, SDXL)/extra_data-vid_2829653/model_dict-mid_161431-vid_2829653.json

@@ -0,0 +1,918 @@
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klein-9b/lora/Ultra Real - Klein 9b/extra_data-vid_2846977/127044477.json

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klein-9b/lora/Ultra Real - Klein 9b/extra_data-vid_2846977/model_dict-mid_2462105-vid_2846977.json

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+  "description": "<p><strong>❤️ Please Consider Supporting My Work</strong><br /><span style=\"color:rgb(134, 142, 150)\">I love building open tools and LoRA models for everyone. If you find this useful, consider supporting me with a coffee. It helps me create even better and more models!</span><br /><span style=\"background-color:rgb(26, 27, 30);color:rgb(141, 141, 143);font-family:-apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, Roboto, Helvetica, Arial, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;;font-size:16px\">👉 </span><a target=\"_blank\" rel=\"ugc\" href=\"https://ko-fi.com/vizsumit\"><strong>https://ko-fi.com/vizsumit</strong></a></p><hr /><p><strong>LoRA </strong>designed to reduce the typical <em>smooth/plastic AI look</em> and add more <strong>natural skin texture and realism</strong> to images. It works especially well for <strong>close-ups and medium shots</strong> where skin detail is important.</p><p>You can also use for <strong>upscaling </strong>too or restoring old photos, which actually intended for.</p><p></p><p><span style=\"color:rgb(250, 176, 5)\"><strong>Version Comparison</strong></span></p><p><span style=\"color:rgb(34, 139, 230)\"><strong><em>OVERVIEW </em></strong></span><strong><em>= V4:</em></strong><em> More quality + NSFW detailing </em>support<em>, </em><strong><em>V3:</em></strong><em> Professional/Celebrity Skin,</em><strong><em> V2:</em></strong><em> Realistic Natural Skin, </em><strong><em>V1:</em></strong><em> Too Much Details</em></p><p><span style=\"color:rgb(250, 176, 5)\"><strong>V4</strong></span><strong> </strong>is trained on more refined and 50% nsfw dataset, so besides better quality it has NSFW detailing capabilities too.<em> </em><span style=\"color:rgb(250, 82, 82)\"><em>Note:</em></span><em> </em><span style=\"color:rgb(250, 82, 82)\"><em>This is only for detailing, for simple nsfw use nsfw words in prompt, for hardcore stuff use other loras with it.</em></span></p><p><span style=\"color:rgb(250, 176, 5)\"><strong>V3</strong></span><strong> </strong>is trained on professional 4K quality images with higher steps. It applies very subtle skin texture which looks more realistic, without producing freckles and burnes.</p><p><span style=\"color:rgb(250, 176, 5)\"><strong>V2</strong></span><strong> </strong>for more natural looking skin texture than, can produce freckles and moles for some time. It is good at preserving skin tone and lighting also.</p><p><span style=\"color:rgb(250, 176, 5)\"><strong>V1</strong></span><strong> </strong>tends to produce overdone skin texture like more pores and freckles, and it can change lighting and skin tone also.</p><hr /><p><strong>🛠️ Editing Workflow - </strong><a target=\"_blank\" rel=\"ugc\" href=\"https://github.com/vizsumit/comfyui-workflows\">https://github.com/vizsumit/comfyui-workflows</a></p><p><span style=\"color:rgb(250, 176, 5)\"><strong>V4</strong></span><strong> </strong>Weight: <strong>0.55, </strong>Prompt: <code>Make this photo high-quality. Preserve subject's face, expression, figure and pose. Preserve overall composition of this photo.</code></p><p><span style=\"color:rgb(250, 176, 5)\"><strong>V3</strong></span> Weight: <strong>0.6, </strong>Prompt: <code>Make this photo high-quality. Preserve subject's face, expression, figure and pose. Preserve overall composition of this photo.</code></p><p><span style=\"color:rgb(250, 176, 5)\"><strong>V2</strong></span> Weight: <strong>0.6, </strong>Prompt: <code>Make this photo high-quality with natural skin texture. Preserve subject's facial features, expression, figure and pose. Preserve overall composition of this photo.</code></p><p><span style=\"color:rgb(250, 176, 5)\"><strong>V1</strong></span> Weight: <strong>0.5, </strong>Prompt: <code>Make this photo high-quality featuring realstic skin texture. Preserve subject's facial features, expression, figure and pose. Preserve overall composition of this photo.</code></p><hr /><p><strong>🖼️ Generation Workflow - </strong><a target=\"_blank\" rel=\"ugc\" href=\"https://github.com/vizsumit/comfyui-workflows\">https://github.com/vizsumit/comfyui-workflows</a></p><p>Weight: <strong>0.7-0.8</strong></p><p><span style=\"color:rgb(250, 176, 5)\"><strong>V4</strong></span> Prompt: <code>This is a high-quality photograph of a (your subject...)</code></p><p><span style=\"color:rgb(250, 176, 5)\"><strong>V3 </strong></span>Prompt: <code>A high-quality photograph of a (your subject...)</code></p><p><span style=\"color:rgb(250, 176, 5)\"><strong>V2</strong></span> Prompt: <code>A high-quality medium close-up photo with realistic skin texture featuring a (your subject...)</code></p><p><span style=\"color:rgb(250, 176, 5)\"><strong>V1 </strong></span>Prompt: <code>This is a high-quality photo with realistic skin texture and details of a (your subject...)</code></p><hr /><p>Feel free to try it and share results or feedback. 🙂</p>",
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