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  1. C-游戏角色/女王之刃/siggy.civitai.info +593 -0
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  3. C-游戏角色/女王之刃/siggy.safetensors +3 -0
  4. C-游戏角色/碧蓝航线/atago_azurlane.civitai.info +247 -0
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  6. C-游戏角色/碧蓝航线/atago_azurlane.safetensors +3 -0
  7. C-游戏角色/碧蓝航线/sirius_azurlane.civitai.info +179 -0
  8. C-/346/270/270/346/210/217/350/247/222/350/211/262//347/242/247/350/223/235/350/210/252/347/272/277/sirius_azurlane.preview.png +0 -0
  9. C-游戏角色/碧蓝航线/sirius_azurlane.safetensors +3 -0
  10. C-游戏角色/碧蓝航线/taiho_azurlane.civitai.info +264 -0
  11. C-/346/270/270/346/210/217/350/247/222/350/211/262//347/242/247/350/223/235/350/210/252/347/272/277/taiho_azurlane.preview.png +0 -0
  12. C-游戏角色/碧蓝航线/taiho_azurlane.safetensors +3 -0
  13. C-游戏角色/碧蓝航线/unicorn_azurlane.civitai.info +162 -0
  14. C-/346/270/270/346/210/217/350/247/222/350/211/262//347/242/247/350/223/235/350/210/252/347/272/277/unicorn_azurlane.preview.png +0 -0
  15. C-游戏角色/碧蓝航线/unicorn_azurlane.safetensors +3 -0
  16. C-游戏角色/精灵宝可梦/sango.civitai.info +488 -0
  17. C-/346/270/270/346/210/217/350/247/222/350/211/262//347/262/276/347/201/265/345/256/235/345/217/257/346/242/246/sango.preview.png +0 -0
  18. C-游戏角色/精灵宝可梦/sango.safetensors +3 -0
C-游戏角色/女王之刃/siggy.civitai.info ADDED
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+ "description": "<p><strong>NOTE: ALL CHARACTERS IN THE IMAGES ARE ADULTS.</strong></p>\n<h2>How to Use This Model</h2>\n<p><strong>USE THEM SIMULTANEOUSLY</strong>. In this case, you need to download both <code>atago_azurlane.pt</code> and \n<code>atago_azurlane.safetensors</code>, then <strong>use <code>atago_azurlane.pt</code> as texture inversion embedding, and use\n<code>atago_azurlane.safetensors</code> as LoRA at the same time</strong>.</p>\n<p><strong>\u305d\u308c\u3089\u3092\u540c\u6642\u306b\u4f7f\u7528\u3057\u3066\u304f\u3060\u3055\u3044</strong>\u3002\u3053\u306e\u5834\u5408\u3001<code>atago_azurlane.pt</code>\u3068<code>atago_azurlane.safetensors</code>\u306e\u4e21\u65b9\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\n\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<code>atago_azurlane.pt</code>\u3092\u30c6\u30af\u30b9\u30c1\u30e3\u53cd\u8ee2\u57cb\u3081\u8fbc\u307f\u3068\u3057\u3066\u4f7f\u7528\u3057\u3001\u540c\u6642\u306b<code>atago_azurlane.safetensors</code>\u3092LoRA\u3068\u3057\u3066\u4f7f\u7528\u3057\u3066\u304f\u3060\u3055\u3044\u3002</p>\n<p><strong>\u540c\u65f6\u4f7f\u7528\u5b83\u4eec</strong>\u3002\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u60a8\u9700\u8981\u4e0b\u8f7d<code>atago_azurlane.pt</code>\u548c<code>atago_azurlane.safetensors</code>\u8fd9\u4e24\u4e2a\u6587\u4ef6\uff0c\u7136\u540e\u5c06<code>atago_azurlane.pt</code>\u7528\u4f5c\u7eb9\u7406\u53cd\u8f6c\u5d4c\u5165\uff0c\n\u540c\u65f6\u4f7f\u7528<code>atago_azurlane.safetensors</code>\u4f5c\u4e3aLoRA\u3002</p>\n<p>(Translated with ChatGPT)</p>\n<p>The trigger word is <code>atago_azurlane</code>, and the recommended tags are <code>masterpiece, best quality, highres, solo, {atago_azurlane:1.10}, animal_ears, black_hair, long_hair, breasts, large_breasts, bangs, mole_under_eye, mole, extra_ears, ribbon, smile, brown_eyes, blush, white_ribbon, hair_ribbon, swept_bangs, closed_mouth, yellow_eyes</code>.</p>\n<h2>How This Model Is Trained</h2>\n<p>This model is trained with <a href=\"https://github.com/7eu7d7/HCP-Diffusion\" rel=\"ugc\">HCP-Diffusion</a>. \nAnd the auto-training framework is maintained by <a href=\"https://huggingface.co/deepghs\" rel=\"ugc\">DeepGHS Team</a>.</p>\n<h2>Why Some Preview Images Not Look Like Atago Azurlane</h2>\n<p><strong>All the prompt texts</strong> used on the preview images (which can be viewed by clicking on the images) \n<strong>are automatically generated using clustering algorithms</strong> based on feature information extracted from the \ntraining dataset. The seed used during image generation is also randomly generated, and the images have \nnot undergone any selection or modification. As a result, there is a possibility of the mentioned \nissues occurring.</p>\n<p>In practice, based on our internal testing, most models that experience such issues perform better in \nactual usage than what is seen in the preview images. <strong>The only thing you may need to do is fine-tune \nthe tags you use</strong>.</p>\n<h2>I Felt This Model May Be Overfitting or Underfitting, What Shall I Do</h2>\n<p>Our model has been published on <a href=\"https://huggingface.co/CyberHarem/atago_azurlane\" rel=\"ugc\">huggingface repository - CyberHarem/atago_azurlane</a>, where\nmodels of all the steps are saved. Also, we published the training dataset on \n<a href=\"https://huggingface.co/datasets/CyberHarem/atago_azurlane\" rel=\"ugc\">huggingface dataset - CyberHarem/atago_azurlane</a>, which may be helpful to you.</p>\n<h2>Why Not Just Using The Better-Selected Images</h2>\n<p>Our model's entire process, from data crawling, training, to generating preview images and publishing, \nis <strong>100% automated without any human intervention</strong>. It's an interesting experiment conducted by our team, \nand for this purpose, we have developed a complete set of software infrastructure, including data filtering, \nautomatic training, and automated publishing. Therefore, if possible, we would appreciate more feedback or \nsuggestions as they are highly valuable to us.</p>",
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+ "name": "unicorn/\u30e6\u30cb\u30b3\u30fc\u30f3/\u72ec\u89d2\u517d (Azur Lane)",
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+ "description": "<p><strong>NOTE: ALL CHARACTERS IN THE IMAGES ARE ADULTS.</strong></p>\n<h2>How to Use This Model</h2>\n<p><strong>USE THEM SIMULTANEOUSLY</strong>. In this case, you need to download both <code>unicorn_azurlane.pt</code> and \n<code>unicorn_azurlane.safetensors</code>, then <strong>use <code>unicorn_azurlane.pt</code> as texture inversion embedding, and use\n<code>unicorn_azurlane.safetensors</code> as LoRA at the same time</strong>.</p>\n<p><strong>\u305d\u308c\u3089\u3092\u540c\u6642\u306b\u4f7f\u7528\u3057\u3066\u304f\u3060\u3055\u3044</strong>\u3002\u3053\u306e\u5834\u5408\u3001<code>unicorn_azurlane.pt</code>\u3068<code>unicorn_azurlane.safetensors</code>\u306e\u4e21\u65b9\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\n\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<code>unicorn_azurlane.pt</code>\u3092\u30c6\u30af\u30b9\u30c1\u30e3\u53cd\u8ee2\u57cb\u3081\u8fbc\u307f\u3068\u3057\u3066\u4f7f\u7528\u3057\u3001\u540c\u6642\u306b<code>unicorn_azurlane.safetensors</code>\u3092LoRA\u3068\u3057\u3066\u4f7f\u7528\u3057\u3066\u304f\u3060\u3055\u3044\u3002</p>\n<p><strong>\u540c\u65f6\u4f7f\u7528\u5b83\u4eec</strong>\u3002\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u60a8\u9700\u8981\u4e0b\u8f7d<code>unicorn_azurlane.pt</code>\u548c<code>unicorn_azurlane.safetensors</code>\u8fd9\u4e24\u4e2a\u6587\u4ef6\uff0c\u7136\u540e\u5c06<code>unicorn_azurlane.pt</code>\u7528\u4f5c\u7eb9\u7406\u53cd\u8f6c\u5d4c\u5165\uff0c\n\u540c\u65f6\u4f7f\u7528<code>unicorn_azurlane.safetensors</code>\u4f5c\u4e3aLoRA\u3002</p>\n<p>(Translated with ChatGPT)</p>\n<p>The trigger word is <code>unicorn_azurlane</code>, and the recommended tags are <code>masterpiece, best quality, highres, solo, {unicorn_azurlane:1.10}, purple_hair, long_hair, purple_eyes, bangs, blush, ahoge, very_long_hair, ribbon, hair_bun, single_hair_bun, hair_ribbon, stuffed_toy, single_side_bun, stuffed_animal, stuffed_winged_unicorn, one_side_up, breasts, hair_ornament</code>.</p>\n<h2>How This Model Is Trained</h2>\n<p>This model is trained with <a href=\"https://github.com/7eu7d7/HCP-Diffusion\" rel=\"ugc\">HCP-Diffusion</a>. \nAnd the auto-training framework is maintained by <a href=\"https://huggingface.co/deepghs\" rel=\"ugc\">DeepGHS Team</a>.</p>\n<h2>Why Some Preview Images Not Look Like Unicorn Azurlane</h2>\n<p><strong>All the prompt texts</strong> used on the preview images (which can be viewed by clicking on the images) \n<strong>are automatically generated using clustering algorithms</strong> based on feature information extracted from the \ntraining dataset. The seed used during image generation is also randomly generated, and the images have \nnot undergone any selection or modification. As a result, there is a possibility of the mentioned \nissues occurring.</p>\n<p>In practice, based on our internal testing, most models that experience such issues perform better in \nactual usage than what is seen in the preview images. <strong>The only thing you may need to do is fine-tune \nthe tags you use</strong>.</p>\n<h2>I Felt This Model May Be Overfitting or Underfitting, What Shall I Do</h2>\n<p>Our model has been published on <a href=\"https://huggingface.co/CyberHarem/unicorn_azurlane\" rel=\"ugc\">huggingface repository - CyberHarem/unicorn_azurlane</a>, where\nmodels of all the steps are saved. Also, we published the training dataset on \n<a href=\"https://huggingface.co/datasets/CyberHarem/unicorn_azurlane\" rel=\"ugc\">huggingface dataset - CyberHarem/unicorn_azurlane</a>, which may be helpful to you.</p>\n<h2>Why Not Just Using The Better-Selected Images</h2>\n<p>Our model's entire process, from data crawling, training, to generating preview images and publishing, \nis <strong>100% automated without any human intervention</strong>. It's an interesting experiment conducted by our team, \nand for this purpose, we have developed a complete set of software infrastructure, including data filtering, \nautomatic training, and automated publishing. Therefore, if possible, we would appreciate more feedback or \nsuggestions as they are highly valuable to us.</p>",
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