Stable Diffusion 大模型资源下载集合
## Stable Diffusion### Stable Diffusion v2.0
Stable Diffusion 2.0 源码
https://github.com/Stability-AI/stablediffusion
768x768 模型
https://huggingface.co/stabilityai/stable-diffusion-2
512x512 基础模型
https://huggingface.co/stabilityai/stable-diffusion-2-base
深度模型
https://huggingface.co/stabilityai/stable-diffusion-2-depth
4倍放大器
https://huggingface.co/stabilityai/stable-diffusion-x4-upscaler
### Stable Diffusion v1.5
> “Stable-Diffusion-v1-5”checkpoint是使用“Stable-Diffusion-v1-2”检查点的权重进行初始化的，随后在“laion-aesthetics v2 5+”数据集上进行了512x512分辨率的595k步微调，并且减少了10％的文本条件，以改善无分类器的引导采样。仓库地址为 [https://huggingface.co/runwayml/stable-diffusion-v1-5。](https://huggingface.co/runwayml/stable-diffusion-v1-5%E3%80%82)
!!! 注释
v1-5-pruned-emaonly.ckpt **** | **SHA256** cc6cb27103417325ff94f52b7a5d2dde45a7515b25c255d8e396c90014281516
v1-5-pruned.ckpt **** | **SHA256** e1441589a6f3c5a53f5f54d0975a18a7feb7cdf0b0dee276dfc3331ae376a053
**磁力链下载 v1-5-pruned-emaonly.ckpt**
```text
magnet:?xt=urn:btih:2daef5b5f63a16a9af9169a529b1a773fc452637&dn=v1-5-pruned-emaonly.ckpt&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337%2fannounce&tr=udp%3a%2f%2f9.rarbg.com%3a2810%2fannounce&tr=udp%3a%2f%2ftracker.openbittorrent.com%3a6969%2fannounce&tr=udp%3a%2f%2fopentracker.i2p.rocks%3a6969%2fannounce&tr=https%3a%2f%2fopentracker.i2p.rocks%3a443%2fannounce&tr=http%3a%2f%2ftracker.openbittorrent.com%3a80%2fannounce&tr=udp%3a%2f%2ftracker.torrent.eu.org%3a451%2fannounce&tr=udp%3a%2f%2fopen.stealth.si%3a80%2fannounce&tr=udp%3a%2f%2fvibe.sleepyinternetfun.xyz%3a1738%2fannounce&tr=udp%3a%2f%2ftracker2.dler.org%3a80%2fannounce&tr=udp%3a%2f%2ftracker1.bt.moack.co.kr%3a80%2fannounce&tr=udp%3a%2f%2ftracker.zemoj.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.tiny-vps.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.theoks.net%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.publictracker.xyz%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.monitorit4.me%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.moeking.me%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.lelux.fi%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.dler.org%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.army%3a6969%2fannounce
```
**Web下载 v1-5-pruned-emaonly.ckpt**
```text
https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt
```
**磁力链下载 v1-5-pruned.ckpt**
!!! 警告
此版本的模型仅适用于原生训练。如果您不知道这是什么，您就不需要使用此版本。
如果您只想生成图像或训练Dreambooth / 文本反演 / 超网络，请使用v1-5-pruned-emaonly.ckpt。
```text
magnet:?xt=urn:btih:38c2b7a8abf55604ae8a5f060ffda2e028075af3&dn=v1-5-pruned.ckpt&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337%2fannounce&tr=udp%3a%2f%2f9.rarbg.com%3a2810%2fannounce&tr=udp%3a%2f%2ftracker.openbittorrent.com%3a6969%2fannounce&tr=udp%3a%2f%2fopentracker.i2p.rocks%3a6969%2fannounce&tr=https%3a%2f%2fopentracker.i2p.rocks%3a443%2fannounce&tr=http%3a%2f%2ftracker.openbittorrent.com%3a80%2fannounce&tr=udp%3a%2f%2ftracker.torrent.eu.org%3a451%2fannounce&tr=udp%3a%2f%2fopen.stealth.si%3a80%2fannounce&tr=udp%3a%2f%2fvibe.sleepyinternetfun.xyz%3a1738%2fannounce&tr=udp%3a%2f%2ftracker2.dler.org%3a80%2fannounce&tr=udp%3a%2f%2ftracker1.bt.moack.co.kr%3a80%2fannounce&tr=udp%3a%2f%2ftracker.zemoj.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.tiny-vps.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.theoks.net%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.publictracker.xyz%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.monitorit4.me%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.moeking.me%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.lelux.fi%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.dler.org%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.army%3a6969%2fannounce
```
**Web下载 v1-5-pruned.ckpt**
Requires login.
!!! 警告
此版本的模型仅适用于原生训练。如果您不知道这是什么，您不需要使用此版本。
如果您只想生成图像或训练Dreambooth / 文本反演 / 超网络，请改为使用v1-5-pruned-emaonly.ckpt。
```text
https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned.ckpt
```
### Stable Diffusion VAE ft-mse-original
从ft-EMA恢复并使用EMA权重，使用重新加权的损失进行另外280k步训练，更加重视MSE重建（产生了稍微“平滑”一些的输出）。为了保持与现有模型的兼容性，只有解码器部分进行了微调；这些检查点可以用作现有自编码器的即插即用替代品。
仓库及信息（包括比较）：[https://huggingface.co/stabilityai/sd-vae-ft-mse-original](https://huggingface.co/stabilityai/sd-vae-ft-mse-original)
!!! 警告
VAE与列表中的其他模型不同。它不是一个可以单独用于生成图像的完整模型，而是一个与其他模型配合使用的组件。
如果您不知道这是什么或者为什么需要它，请不要理会它。
**Web下载**
```text
https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt
```
### Stable Diffusion VAE ft-ema-original
从原始检查点中恢复，训练了313198步，并使用EMA权重。为了保持与现有模型的兼容性，只有解码器部分进行了微调；这些检查点可以用作现有自编码器的即插即用替代品。
仓库及信息（包括比较）：[https://huggingface.co/stabilityai/sd-vae-ft-ema-original](https://huggingface.co/stabilityai/sd-vae-ft-ema-original)
!!! 警告
VAE与列表中的其他模型不同。它不是一个可以单独用于生成图像的完整模型，而是一个与其他模型配合使用的组件。
如果您不知道这是什么或者为什么需要它，请不要理会它。
**Web**
```text
https://huggingface.co/stabilityai/sd-vae-ft-ema-original/resolve/main/vae-ft-ema-560000-ema-pruned.ckpt
```
### Stable Diffusion Inpainting v1.5
仓库链接 [https://huggingface.co/runwayml/stable-diffusion-inpainting](https://huggingface.co/runwayml/stable-diffusion-inpainting)
旨在与 [https://github.com/runwayml/stable-diffusion](https://github.com/runwayml/stable-diffusion) 一起使用。
> Stable-Diffusion-Inpainting 是用 Stable-Diffusion-v-1-2 的权重初始化的。首先进行了 595k 步的常规训练，然后进行了 440k 步的修复训练，在“laion-aesthetics v2 5+”上的分辨率为512x512，并减少了10%的文本调节，以改进无分类器指导采样。对于修复，UNet具有5个额外的输入通道（4个用于编码的遮罩图像，1个用于遮罩本身），在恢复非修复检查点后进行零初始化权重。在训练期间，我们生成合成遮罩，并在25%的情况下对所有内容进行遮罩。
!!! 注释
**SHA256** c6bbc15e3224e6973459ba78de4998b80b50112b0ae5b5c67113d56b4e366b19
**Torrent**
```text
magnet:?xt=urn:btih:b523a9e71ae02e27b28007eca190f41999c2add1&dn=sd-v1-5-inpainting.ckpt&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337%2fannounce&tr=udp%3a%2f%2f9.rarbg.com%3a2810%2fannounce&tr=udp%3a%2f%2ftracker.openbittorrent.com%3a6969%2fannounce&tr=http%3a%2f%2ftracker.openbittorrent.com%3a80%2fannounce&tr=udp%3a%2f%2fopentracker.i2p.rocks%3a6969%2fannounce&tr=https%3a%2f%2fopentracker.i2p.rocks%3a443%2fannounce&tr=udp%3a%2f%2ftracker.torrent.eu.org%3a451%2fannounce&tr=udp%3a%2f%2fopen.stealth.si%3a80%2fannounce&tr=udp%3a%2f%2fvibe.sleepyinternetfun.xyz%3a1738%2fannounce&tr=udp%3a%2f%2ftracker2.dler.org%3a80%2fannounce&tr=udp%3a%2f%2ftracker1.bt.moack.co.kr%3a80%2fannounce&tr=udp%3a%2f%2ftracker.zemoj.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.tiny-vps.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.theoks.net%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.swateam.org.uk%3a2710%2fannounce&tr=udp%3a%2f%2ftracker.publictracker.xyz%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.pomf.se%3a80%2fannounce&tr=udp%3a%2f%2ftracker.monitorit4.me%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.moeking.me%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.lelux.fi%3a6969%2fannounce
```
**Web**
Requires login
```text
https://huggingface.co/runwayml/stable-diffusion-inpainting/resolve/main/sd-v1-5-inpainting.ckpt
```
### Stable Diffusion v1.4
!!! 注释
sd-v1-4-pruned.ckpt ****
sd-v1-4.ckpt **** | **SHA256** fe4efff1e174c627256e44ec2991ba279b3816e364b49f9be2abc0b3ff3f8556
sd-v1-4-full-ema.ckpt **** | **SHA256** 14749efc0ae8ef0329391ad4436feb781b402f4fece4883c7ad8d10556d8a36a
**磁力链**
```text
magnet:?xt=urn:btih:3A4A612D75ED088EA542ACAC52F9F45987488D1C&tr=udp://tracker.opentrackr.org:1337
```
**HuggingFace**
Requires login.
```text
https://huggingface.co/CompVis/stable-diffusion-v-1-4-original
```
**GDrive**
```text
https://drive.google.com/file/d/1wHFgl0ivCmIZv88hVZXkb8oy9qCuaBGA/view
```
## Waifu Diffusion
### Waifu Diffusion VAE kl-f8-anime2
对 SD 1.4 VAE 模型在 25 万张动漫风格图像上进行了微调，据说可以改善眼睛和手指的重建效果。
信息 `https://twitter.com/haruu1367/status/1579286947519864833`
存储库 `https://huggingface.co/hakurei/waifu-diffusion-v1-4`
！！！警告
VAE 不同于列表中的其他模型。它不是可以单独用于生成图像的完整模型，而是与其他模型配合使用的组件。
如果您不知道这是什么或为什么需要它，请不要使用它。
**Web**
```text
https://huggingface.co/hakurei/waifu-diffusion-v1-4/resolve/main/vae/kl-f8-anime2.ckpt
```
### Waifu Diffusion VAE kl-f8-anime
一种在250k个动漫风格图像上对SD 1.4 VAE进行微调的方法，据称可以改善眼睛和手指的重建。信息在 `https://twitter.com/haruu1367/status/1579286947519864833`，代码在 `https://huggingface.co/hakurei/waifu-diffusion-v1-4`。
!!! 警告
VAE不同于列表中的其他模型。它不能单独用于生成图像，而是要与其他模型一起使用的组件。
如果您不知道这是什么或者为什么需要它，请不要费心。
**Web**
```text
https://huggingface.co/hakurei/waifu-diffusion-v1-4/resolve/main/vae/kl-f8-anime.ckpt
```
### Waifu Diffusion v1.3 Full
该模型是在600,000个高分辨率Danbooru图像上进行了10个Epoch的训练的1.3 Waifu Diffusion模型。发布说明可以在此链接中找到：[https://gist.github.com/harubaru/f727cedacae336d1f7877c4bbe2196e1](https://gist.github.com/harubaru/f727cedacae336d1f7877c4bbe2196e1)
!!! note
wd-v1-3-float16.ckpt **** | **SHA256** 4afab9126057859b34d13d6207d90221d0b017b7580469ea70cee37757a29edd
wd-v1-3-float32.ckpt **** | **SHA256** 9dade826203c7ee369881b5dc20d34298fa644c1f137568e09fbc4b9a0d3e817
wd-v1-3-full.ckpt **** | **SHA256** 23ba8d0411c211d3d14903d46613bc088924e1453ed1c6428ce86bde54a37d27
wd-v1-3-full-opt.ckpt **** | **SHA256** 10912b9a6d773ea7c299c0563d10538ada04ade81837362b6c0c67be4df937c1
**wd-v1-3-float16.ckpt Web**
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/wd-v1-3-float16.ckpt
```
**wd-v1-3-float32.ckpt Web**
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/wd-v1-3-float32.ckpt
```
**wd-v1-3-full.ckpt Web**
这里提到的完整EMA比较大是因为它包含了仅用于训练的附加数据（**training only**）。如果您不知道这是什么，请使用float16或float32版本即可。
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/wd-v1-3-full.ckpt
```
**wd-v1-3-full-opt.ckpt Web**
完整的opt文件大小较大，因为它包含仅用于训练的其他数据（**training only**）。
如果您不知道这是什么，请使用float16或float32版本
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/wd-v1-3-full-opt.ckpt
```
### Waifu Diffusion v1.3 beta epoch09
**==未完成的Beta版本==** 使用600,000张高分辨率Danbooru图像在9个Epochs上训练的1.3 Waifu Diffusion模型。
model-epoch08-float16.ckpt **** | **SHA256** b30bab13a2ea946ba85bc7b3a30c3fa20d013ca306193aa54b4771d147192dc1
model-epoch08-float32.ckpt **** | **SHA256** a16d2f57b229156a61ccab6b1cbc120332f3a2a320c75952241e6439f3fe79ec
model-epoch08-full.ckpt **** | **SHA256** 7fb9c64bb460724dfecbf693fcd8e0e556c4664553a352c1256997813d585329
**model-epoch09-float16.ckpt Web**
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/model-epoch09-float16.ckpt
```
**model-epoch09-float32.ckpt Web**
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/model-epoch09-float32.ckpt
```
**model-epoch09-full.ckpt Web**
The full EMA is larger in file size because it contains additional data used for **training only**.
If you don't know what this is, use the float16 or float32 version.
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/model-epoch09-full.ckpt
```
### Waifu Diffusion v1.3 beta epoch08
**==未完成测试版==** 基于60万张高分辨率Danbooru图像训练的1.3 Waifu Diffusion模型，训练了8个Epoch。
!!! note
model-epoch08-float16.ckpt **** | **SHA256** 3a3a36aac85502a06878ec6760c0fb95f71546ad734fbb2b6cfab9a50db7aa8d
model-epoch08-float32.ckpt **** | **SHA256** e64cbc29edbef82142768c3a398345f602ba8b337ebd22cd83071162fe789a18
model-epoch08-full.ckpt **** | **SHA256** c2a8b09f77ce572c012c810495d8ae9f989d04ca6b3226c93be5dce2208bacdd
**model-epoch08-float16.ckpt Web**
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/model-epoch08-float16.ckpt
```
**model-epoch08-float32.ckpt Web**
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/model-epoch08-float32.ckpt
```
**model-epoch08-full.ckpt Web**
“full EMA” 的文件大小更大，因为它包含了仅用于训练的额外数据。如果您不知道这是什么，请使用 float16 或 float32 版本。
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/model-epoch08-full.ckpt
```
### Waifu Diffusion v1.3 beta epoch07
**==未完成测试版==** 在600,000张高分辨率的Danbooru图像上进行了7个Epoch的训练的1.3 Waifu Diffusion模型。
> 该模型还没有完成，离完成还很远。不要将结果视为最终结果。
!!! note
model-epoch07-float16.ckpt **** | **SHA256** 0aa0a2d1620b65fbcfe800ac5d5b5fc681c9e3bc7373ad5519837f94828eb83f
model-epoch07-float32.ckpt **** | **SHA256** 99c1061162c126c59d17cfddaf8b475935a9f0a504f7b305b1d733e7618be82b
model-epoch07-full.ckpt **** | **SHA256** 74ae340acb9ac251b8b9ee57f795e18bc4d39c016272fafd440e637fe391a790
**model-epoch07-float16.ckpt Web**
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/model-epoch07-float16.ckpt
```
**model-epoch07-float32.ckpt Web**
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/model-epoch07-float32.ckpt
```
**model-epoch07-full.ckpt Web**
The full EMA is larger in file size because it contains additional data used for **training only**.
If you don't know what this is, use the float16 or float32 version.
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/model-epoch07-full.ckpt
```
### Waifu Diffusion v1.3 beta epoch06
**==未完成的测试版==** 在 600,000 张高分辨率 Danbooru 图像上训练了 6 个 Epochs 的 1.3 Waifu Diffusion 模型。
> 该模型还没有完成，离完成还很远。不要将结果视为最终结果。
!!! note
model-epoch06-float16.ckpt **** | **SHA256** c0397df53cd4cf1cfadb95a121a67eaad903e4203d708abfe3409a832a517191
model-epoch06-float32.ckpt **** | **SHA256** f34c89c80e91d77c06df178d292611ac7757728dd7a3aaff8c4c9117e6e92e35
model-epoch06-full.ckpt **** | **SHA256** cc5569691c843f64cc8e819b78c0081f6e8024432f6de898f11ee816ac3ff5ca
**model-epoch06-float16.ckpt Web**
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/model-epoch06-float16.ckpt
```
**model-epoch06-float32.ckpt Web**
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/model-epoch06-float32.ckpt
```
**model-epoch06-full.ckpt Web**
The full EMA is larger in file size because it contains additional data used for **training only**.
If you don't know what this is, use the float16 or float32 version.
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/model-epoch06-full.ckpt
```
### Waifu Diffusion v1.3 beta epoch05
**==未完成测试版==** 1.3 Waifu Diffusion 模型使用 60 万高分辨率 Danbooru 图像进行了 5 个 Epochs 的训练。
> 该模型还没有完成，离完成还很远。不要将结果视为最终结果。
!!! note
model-epoch05-float16.ckpt **** | **SHA256** 26cf2a2e30095926bb9fd9de0c83f47adc0b442dbfdc3d667d43778e8b70bece
model-epoch05-float32.ckpt **** | **SHA256** 694617b2145abcd248d78ea2c556af86787ef9f79e9d9a0f7473d7b408dd3dfa
model-epoch05-full.ckpt **** | **SHA256** e0fceaac42328912ed60957c5fed129a418bdd5f3ebe82d5f09e7901a296a6ce
**model-epoch05-float16.ckpt Web**
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/model-epoch05-float16.ckpt
```
**model-epoch05-float32.ckpt Web**
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/model-epoch05-float32.ckpt
```
**model-epoch05-full.ckpt Web**
The full EMA is larger in file size because it contains additional data used for **training only**.
If you don't know what this is, use the float16 or float32 version.
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/model-epoch05-full.ckpt
```
### Waifu Diffusion v1.3 beta epoch04
**==未完成的Beta版本==** ，使用了600,000张高分辨率的Danbooru图片训练的1.3 Waifu Diffusion模型，训练了4个Epochs。
> 该模型还没有完成，离完成还很远。不要将结果视为最终结果。
!!! note
model-epoch04-float16.ckpt **** | **SHA256** 3fd4bbb7ca76c806d88061f0ce994b763693369bd6ea37863c93c1c6b9d25232
model-epoch04-float32.ckpt **** | **SHA256** 5237503095524512c7612f81ef786036aa001fd76693064fb00478115659a335
model-epoch04-full.ckpt **** | **SHA256** eee5a4391d6074f08bc6c3de3457c245252bde101e3e651c27b5cf85d4926b08
**model-epoch04-float16.ckpt Web**
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/model-epoch04-float16.ckpt
```
**model-epoch04-float32.ckpt Web**
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/model-epoch04-float32.ckpt
```
**model-epoch04-full.ckpt Web**
The full EMA is larger in file size because it contains additional data used for **training only**.
If you don't know what this is, use the float16 or float32 version.
```
https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/model-epoch04-full.ckpt
```
## Anything-V3.0
动漫模型
信息 [https://www.bilibili.com/read/cv19603218](https://www.bilibili.com/read/cv19603218)
**Torrent fp16 **
```text
magnet:?xt=urn:btih:45cd353ac4fa87098db5e3a6a349539710a3a1f5&dn=Anything-V3.0-fp16.zip&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337%2fannounce&tr=udp%3a%2f%2f9.rarbg.com%3a2810%2fannounce&tr=udp%3a%2f%2fopentracker.i2p.rocks%3a6969%2fannounce&tr=https%3a%2f%2fopentracker.i2p.rocks%3a443%2fannounce&tr=udp%3a%2f%2ftracker.torrent.eu.org%3a451%2fannounce&tr=udp%3a%2f%2fopen.stealth.si%3a80%2fannounce&tr=http%3a%2f%2ftracker.openbittorrent.com%3a80%2fannounce&tr=udp%3a%2f%2fvibe.sleepyinternetfun.xyz%3a1738%2fannounce&tr=udp%3a%2f%2ftracker1.bt.moack.co.kr%3a80%2fannounce&tr=udp%3a%2f%2ftracker.zerobytes.xyz%3a1337%2fannounce&tr=udp%3a%2f%2ftracker.tiny-vps.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.theoks.net%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.swateam.org.uk%3a2710%2fannounce&tr=udp%3a%2f%2ftracker.publictracker.xyz%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.monitorit4.me%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.moeking.me%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.encrypted-data.xyz%3a1337%2fannounce&tr=udp%3a%2f%2ftracker.dler.org%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.army%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.altrosky.nl%3a6969%2fannounce
```
**Torrent fp32 **
```text
magnet:?xt=urn:btih:d9db662ab5ace77004b3348c23c9381380c27156&dn=Anything-V3.0-fp32.zip&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337%2fannounce&tr=udp%3a%2f%2f9.rarbg.com%3a2810%2fannounce&tr=udp%3a%2f%2fopentracker.i2p.rocks%3a6969%2fannounce&tr=https%3a%2f%2fopentracker.i2p.rocks%3a443%2fannounce&tr=udp%3a%2f%2ftracker.torrent.eu.org%3a451%2fannounce&tr=udp%3a%2f%2fopen.stealth.si%3a80%2fannounce&tr=http%3a%2f%2ftracker.openbittorrent.com%3a80%2fannounce&tr=udp%3a%2f%2fvibe.sleepyinternetfun.xyz%3a1738%2fannounce&tr=udp%3a%2f%2ftracker1.bt.moack.co.kr%3a80%2fannounce&tr=udp%3a%2f%2ftracker.zerobytes.xyz%3a1337%2fannounce&tr=udp%3a%2f%2ftracker.tiny-vps.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.theoks.net%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.swateam.org.uk%3a2710%2fannounce&tr=udp%3a%2f%2ftracker.publictracker.xyz%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.monitorit4.me%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.moeking.me%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.encrypted-data.xyz%3a1337%2fannounce&tr=udp%3a%2f%2ftracker.dler.org%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.army%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.altrosky.nl%3a6969%2fannounce
```
**Torrent Full EMA **
```text
magnet:?xt=urn:btih:80460036625fb61dce4bc6e7dab744744309a2a0&dn=Anything-V3.0-fullema.zip&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337%2fannounce&tr=udp%3a%2f%2f9.rarbg.com%3a2810%2fannounce&tr=udp%3a%2f%2fopentracker.i2p.rocks%3a6969%2fannounce&tr=https%3a%2f%2fopentracker.i2p.rocks%3a443%2fannounce&tr=udp%3a%2f%2ftracker.torrent.eu.org%3a451%2fannounce&tr=udp%3a%2f%2fopen.stealth.si%3a80%2fannounce&tr=http%3a%2f%2ftracker.openbittorrent.com%3a80%2fannounce&tr=udp%3a%2f%2fvibe.sleepyinternetfun.xyz%3a1738%2fannounce&tr=udp%3a%2f%2ftracker1.bt.moack.co.kr%3a80%2fannounce&tr=udp%3a%2f%2ftracker.zerobytes.xyz%3a1337%2fannounce&tr=udp%3a%2f%2ftracker.tiny-vps.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.theoks.net%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.swateam.org.uk%3a2710%2fannounce&tr=udp%3a%2f%2ftracker.publictracker.xyz%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.monitorit4.me%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.moeking.me%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.encrypted-data.xyz%3a1337%2fannounce&tr=udp%3a%2f%2ftracker.dler.org%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.army%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.altrosky.nl%3a6969%2fannounce
```
## Cafe Unofficial Instagram TEST 模型
> 该模型是在大约14万张Instagram图片上进行训练的，这些图片主要来自日本的账户（包括cosplay、模特和个人账户）。虽然这个模型本身可以创造出一些逼真的Instagram风格的图片，但为了发挥其全部潜力，建议将其与另一个模型（例如berry或其他模型）合并使用。
**Torrent**
```text
magnet:?xt=urn:btih:eb085b3e22310a338e6ea00172cb887c10c54cbc&dn=cafe-instagram-unofficial-test-epoch-9-140k-images-fp32.ckpt&tr=udp%3A%2F%2Ftracker.openbittorrent.com%3A80&tr=udp%3A%2F%2Fopentor.org%3A2710&tr=udp%3A%2F%2Ftracker.ccc.de%3A80&tr=udp%3A%2F%2Ftracker.blackunicorn.xyz%3A6969&tr=udp%3A%2F%2Ftracker.coppersurfer.tk%3A6969&tr=udp%3A%2F%2Ftracker.leechers-paradise.org%3A6969
```
## Trinart
### trinart_characters_19.2m_stable_diffusion_v1 + VAE
> 这是一个基于stable diffusionv1的模型，它使用约1920万个动漫/漫画风格图像（包括预滚动增强图像）进行训练，并使用大约5万个图像进行最终微调。该模型在给定SDv1模型规范下，在艺术风格的多样性和解剖质量之间寻求一个最佳平衡点。这是与AI小说家/TrinArt服务相同的版本1模型，该服务从9月初到10月14日推出。数据集已经过滤，排除了NSFW或不安全的内容。
!!! note
trinart_characters_it4_v1.ckpt **SHA256** d58058f2c71612aa7492d63ad8e6c32b3159494dc51a29ffe71937cdc49b6681
autoencoder_kl-f8-trinart_characters.ckpt **SHA256** d2dd1c82220e31a72bd9958dda249ed7f94faf875d5123ae3aab7a1950a82a8f
**Web**
```text
https://huggingface.co/naclbit/trinart_characters_19.2m_stable_diffusion_v1/resolve/main/trinart_characters_it4_v1.ckpt
```
**VAE Web**
```text
https://huggingface.co/naclbit/trinart_characters_19.2m_stable_diffusion_v1/resolve/main/autoencoder_kl-f8-trinart_characters.ckpt
```
### trinart2_step115000.ckpt
该 V2 checkpoint使用了 Dropout 技术，在训练数据上增加了 10,000 张图片，并采用了一种新的标记策略，训练时间更长，以提高结果的同时保留原始美学。
!!! note
**SHA256** 776af18775dfccf29725a994df855e7d8f7b8ea525013e3a466f210ec15c8fd4
**Web**
```text
https://huggingface.co/naclbit/trinart_stable_diffusion_v2/resolve/main/trinart2_step115000.ckpt
```
### trinart2_step95000.ckpt
V2 checkpoint使用了dropout，增加了1万张图像，并采用了新的标记策略，并进行了更长时间的训练，以改善结果同时保留原有的美学特征。
!!! note
**SHA256** c1799d22a355ba25c9ceeb6e3c91fc61788c8e274b73508ae8a15877c5dbcf63
**Web**
```text
https://huggingface.co/naclbit/trinart_stable_diffusion_v2/resolve/main/trinart2_step95000.ckpt
```
### trinart2_step60000.ckpt
V2 checkpoint使用了Dropout、多了1万张图像以及采用了新的标签策略，训练时间更长，以提高结果并保持原有的美学风格。
!!! note
**SHA256** 0acc70d6a515cdedbc840e2c06525709a83cb9be8cdfdf1136a6548e9ee8f0fa
**Web**
```text
https://huggingface.co/naclbit/trinart_stable_diffusion_v2/resolve/main/trinart2_step60000.ckpt
```
### trinart_stable_diffusion_epoch3.ckpt
这个模型已经被认为是过时的了，请参考trinart2。
trinart_stable_diffusion是一个SD模型，经过大约3.5个epoch的微调，使用了约30,000张高分辨率的漫画/动画风格的图片。
!!! note
**SHA256** 840bbc99a603d4171963b31eec700abcb6f9545d1374b53eb7f830261494be19
**Web**
```text
https://huggingface.co/naclbit/trinart_stable_diffusion/resolve/main/trinart_stable_diffusion_epoch3.ckpt
```
## Furry
### Furry_epoch4.ckpt
训练数据来自于 e621 的 300k 张图片。
Tag counts: `https://mega.nz/file/co0UlQ5Z#vERcoYTWGJguTsXmysbLq1NL_xBS8txQhVvPI5E3QKE` or `https://pixeldrain.com/u/FQwRjyyk`
!!! note
**MD5** f8ef45a295ef4966682f6e8fc2c6830d
**SHA256** 4160c57f98f1727f5a52cba8c844656fc9061311f9c37daf45e8e0ebe913c987
**Torrent**
```text
magnet:?xt=urn:btih:a9635389ae4c5583b0cc76ec8f6dce35438b3016&dn=furry_epoch4.ckpt&tr=udp%3A%2F%2Ftracker.opentrackr.org%3A1337%2Fannounce&tr=udp%3A%2F%2F9.rarbg.com%3A2810%2Fannounce&tr=udp%3A%2F%2Ftracker.openbittorrent.com%3A6969%2Fannounce&tr=udp%3A%2F%2Fopentracker.i2p.rocks%3A6969%2Fannounce&tr=https%3A%2F%2Fopentracker.i2p.rocks%3A443%2Fannounce&tr=http%3A%2F%2Ftracker.openbittorrent.com%3A80%2Fannounce&tr=udp%3A%2F%2Ftracker.torrent.eu.org%3A451%2Fannounce&tr=udp%3A%2F%2Fopen.stealth.si%3A80%2Fannounce&tr=udp%3A%2F%2Ftracker.tiny-vps.com%3A6969%2Fannounce&tr=udp%3A%2F%2Fzecircle.xyz%3A6969%2Fannounce&tr=udp%3A%2F%2Fyahor.ftp.sh%3A6969%2Fannounce&tr=udp%3A%2F%2Fvibe.sleepyinternetfun.xyz%3A1738%2Fannounce&tr=udp%3A%2F%2Fv2.iperson.xyz%3A6969%2Fannounce&tr=udp%3A%2F%2Fuploads.gamecoast.net%3A6969%2Fannounce&tr=udp%3A%2F%2Ftracker2.dler.org%3A80%2Fannounce&tr=udp%3A%2F%2Ftracker1.bt.moack.co.kr%3A80%2Fannounce&tr=udp%3A%2F%2Ftracker.theoks.net%3A6969%2Fannounce&tr=udp%3A%2F%2Ftracker.tcp.exchange%3A6969%2Fannounce&tr=udp%3A%2F%2Ftracker.swateam.org.uk%3A2710%2Fannounce&tr=udp%3A%2F%2Ftracker.publictracker.xyz%3A6969%2Fannounce&tr=http%3A%2F%2Ftracker.bt4g.com%3A2095%2Fannounce
```
**Web**
```text
https://pixeldrain.com/u/dtYiYN7g
```
**Web**
```text
https://iwiftp.yerf.org/Furry/Software/Stable%20Diffusion%20Furry%20Finetune%20Models/Finetune%20models/furry_epoch4.ckpt
```
### Furry_epoch1.ckpt
训练数据来自于 e621 的 300k 张图片。
Tag counts: `https://mega.nz/file/co0UlQ5Z#vERcoYTWGJguTsXmysbLq1NL_xBS8txQhVvPI5E3QKE` or `https://pixeldrain.com/u/FQwRjyyk`
**Torrent**
```
magnet:?xt=urn:btih:d62bc9a088b206565005cab915a58fd26da1802e&dn=furry_epoch1.ckpt&tr=udp%3A%2F%2Ftracker.opentrackr.org%3A1337%2Fannounce&tr=udp%3A%2F%2F9.rarbg.com%3A2810%2Fannounce&tr=udp%3A%2F%2Ftracker.openbittorrent.com%3A6969%2Fannounce&tr=udp%3A%2F%2Fopentracker.i2p.rocks%3A6969%2Fannounce&tr=https%3A%2F%2Fopentracker.i2p.rocks%3A443%2Fannounce&tr=http%3A%2F%2Ftracker.openbittorrent.com%3A80%2Fannounce&tr=udp%3A%2F%2Ftracker.torrent.eu.org%3A451%2Fannounce&tr=udp%3A%2F%2Fopen.stealth.si%3A80%2Fannounce&tr=udp%3A%2F%2Ftracker.tiny-vps.com%3A6969%2Fannounce&tr=udp%3A%2F%2Fzecircle.xyz%3A6969%2Fannounce&tr=udp%3A%2F%2Fyahor.ftp.sh%3A6969%2Fannounce&tr=udp%3A%2F%2Fvibe.sleepyinternetfun.xyz%3A1738%2Fannounce&tr=udp%3A%2F%2Fv2.iperson.xyz%3A6969%2Fannounce&tr=udp%3A%2F%2Fuploads.gamecoast.net%3A6969%2Fannounce&tr=udp%3A%2F%2Ftracker2.dler.org%3A80%2Fannounce&tr=udp%3A%2F%2Ftracker1.bt.moack.co.kr%3A80%2Fannounce&tr=udp%3A%2F%2Ftracker.theoks.net%3A6969%2Fannounce&tr=udp%3A%2F%2Ftracker.tcp.exchange%3A6969%2Fannounce&tr=udp%3A%2F%2Ftracker.swateam.org.uk%3A2710%2Fannounce&tr=udp%3A%2F%2Ftracker.publictracker.xyz%3A6969%2Fannounce&tr=http%3A%2F%2Ftracker.bt4g.com%3A2095%2Fannounce
```
**Web**
```text
https://iwiftp.yerf.org/Furry/Software/Stable%20Diffusion%20Furry%20Finetune%20Models/Finetune%20models/furry_epoch1.ckpt
```
### Furry_epoch0.ckpt
训练数据来自于 e621 的 300k 张图片。
Tag counts: `https://mega.nz/file/co0UlQ5Z#vERcoYTWGJguTsXmysbLq1NL_xBS8txQhVvPI5E3QKE` or `https://pixeldrain.com/u/FQwRjyyk`
**Web**
```text
https://iwiftp.yerf.org/Furry/Software/Stable%20Diffusion%20Furry%20Finetune%20Models/Finetune%20models/furry_epoch0_ckpt
```
## Cal Arts Style
信息和样本 [https://publicprompts.art/cal-arts-dreambooth-model/](https://publicprompts.art/cal-arts-dreambooth-model/)
触发短语： `CALARTS`
**Web**
```text
https://huggingface.co/PublicPrompts/CALARTS/resolve/main/CALARTS.ckpt
```
### Pixel Landscapes V1
信息和示例请访问 [https://publicprompts.art/pixel-landscapes-v1-dreambooth-model/](https://publicprompts.art/pixel-landscapes-v1-dreambooth-model/)
触发短语：`16-bit-landscape pixel art style`
**Web**
```text
https://huggingface.co/PublicPrompts/16-bit-landscape_PublicPrompts/resolve/main/16-bit-landscape_PublicPrompts.ckpt
```
**Web**
```text
https://drive.google.com/file/d/113V4jfwlgCsAKiMLPgpj0hfdZk1sV5cL/view
```
### MicroWorlds
信息和示例请访问 https://publicprompts.art/microworlds-dreambooth-model/
触发短语：: `microworld render style`
**Web**
```text
https://mega.nz/file/7YJRFbxS#FmTrxB4ayFxUaBz-wiVxHov3YLAUFhObR2JyVwq_p_o
```
**Web**
```text
https://drive.google.com/file/d/1QTUATU3WbYIWX-6ECRypCi1z9TOsXIhG/view?usp=sharing
```
### App Icons Generator V1
信息和示例请访问 https://publicprompts.art/app-icons-generator-v1-dreambooth-model/
触发短语: `SKSKS app icon`
**Web**
```text
https://drive.google.com/file/d/1TNZTQfk0CNZg7nwy033olwOpQAkcglAN/view?usp=sharing
```
### Pixel Art V1
信息和示例请访问 https://publicprompts.art/pixel-art-v1-dreambooth-model/
触发短语: `SKSKS art style`
**Web**
```text
https://drive.google.com/file/d/1HwiqDNm3FyxMNEZLqh7FXsMJv9wmy9bc/view?usp=sharing
```
### VTT RPG
一个与D&D种族和怪物有关的模型集合。
信息和下载链接：[https://huggingface.co/VTTRPGResources](https://huggingface.co/VTTRPGResources)
### Comic Diffusion
代码库 [https://huggingface.co/ogkalu/Comic-Diffusion](https://huggingface.co/ogkalu/Comic-Diffusion) 包括了 6 种漫画风格。
> The tokens for V2 are:
> `charliebo artstyle`
> `holliemengert artstyle`
> `marioalberti artstyle`
> `pepelarraz artstyle`
> `andreasrocha artstyle`
> `jamesdaly artstyle`
**Web**
```text
https://huggingface.co/ogkalu/Comic-Diffusion/resolve/main/comic-diffusion-V2.ckpt
```
### SD_PixelArt_SpriteSheet_Generator
这个模型可以生成四个不同角度的像素艺术精灵表。仓库链接为 [https://huggingface.co/Onodofthenorth/SD_PixelArt_SpriteSheet_Generator。](https://huggingface.co/Onodofthenorth/SD_PixelArt_SpriteSheet_Generator%E3%80%82)
> “PixelartFSS” 用于生成前视图，
> “PixelartRSS” 用于生成右视图，
> “PixelartBSS” 用于生成后视图，
> “PixelartLSS” 用于生成左视图。
**Web**
```text
https://huggingface.co/Onodofthenorth/SD_PixelArt_SpriteSheet_Generator/resolve/main/PixelartSpritesheet_V.1.ckpt
```
### midjourney-v4-diffusion
这是在Midjourney v4图像上进行微调的稳定扩散模型。
使用提示：`mdjrny-v4 style`
存储库链接：[https://huggingface.co/prompthero/midjourney-v4-diffusion](https://huggingface.co/prompthero/midjourney-v4-diffusion)
**Web**
```text
https://huggingface.co/prompthero/midjourney-v4-diffusion/resolve/main/mdjrny-v4.ckpt
```
### BloodborneDiffusion
> 这是一个基于Bloodborne系列风格的Dreamboothed Stable Diffusion模型。总数据集由100张图片组成，并使用runawayml 1.5和新的VAE进行了训练，训练步数为12k步（poly LR1e-6）。Token`Bloodborne Style`将引入新的概念。建议采用k_Euler_a或DPM++ 2M Karras上的20步、CFGS 7进行抽样。Repo [https://huggingface.co/Guizmus/BloodborneDiffusion](https://huggingface.co/Guizmus/BloodborneDiffusion)
**Web**
```text
https://huggingface.co/Guizmus/BloodborneDiffusion/resolve/main/BloodborneStyle-v1.ckpt
```
### samdoesarts_style
> 这是一个基于 Sam Yang（samdoesarts）的作品训练的 Dreambooth 模型。
> 使用 automatic1111 的 Dreambooth 扩展进行训练，
> 13000 步，128 张训练图片（256 翻转），1500 张分类图片，1e-6 的学习率。
> 该模型的标记为 `samdoesarts style`。
**Torrent**
```text
magnet:?xt=urn:btih:7999b19ee45d505354e50c25041f405ca8932a38&dn=samdoesarts_style.ckpt&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337%2fannounce&tr=udp%3a%2f%2f9.rarbg.com%3a2810%2fannounce&tr=udp%3a%2f%2fopentracker.i2p.rocks%3a6969%2fannounce&tr=https%3a%2f%2fopentracker.i2p.rocks%3a443%2fannounce&tr=udp%3a%2f%2ftracker.torrent.eu.org%3a451%2fannounce&tr=udp%3a%2f%2fopen.stealth.si%3a80%2fannounce&tr=udp%3a%2f%2ftracker.tiny-vps.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.pomf.se%3a80%2fannounce&tr=udp%3a%2f%2ftracker.dler.org%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.altrosky.nl%3a6969%2fannounce&tr=udp%3a%2f%2fp4p.arenabg.com%3a1337%2fannounce&tr=udp%3a%2f%2fopen.demonii.com%3a1337%2fannounce&tr=udp%3a%2f%2fmovies.zsw.ca%3a6969%2fannounce&tr=udp%3a%2f%2fipv4.tracker.harry.lu%3a80%2fannounce&tr=udp%3a%2f%2ffe.dealclub.de%3a6969%2fannounce&tr=udp%3a%2f%2fexplodie.org%3a6969%2fannounce&tr=udp%3a%2f%2fexodus.desync.com%3a6969%2fannounce&tr=udp%3a%2f%2fbt1.archive.org%3a6969%2fannounce&tr=udp%3a%2f%2f6ahddutb1ucc3cp.ru%3a6969%2fannounce&tr=https%3a%2f%2ftracker.nanoha.org%3a443%2fannounce
```
**Web**
```text
https://anonfiles.com/JbocEcG4yd/samdoesarts_style_ckpt
```
**Web**
```text
https://pixeldrain.com/u/4s3ntWvR
```
### JWST Deep Space Diffusion
> 这是一个基于v1.5的Fine-tuned Stable Diffusion模型，使用詹姆斯·韦伯太空望远镜拍摄的图像和Judy Schmidt的图像进行训练。在提示中使用标记JWST来使用该样式（例如，`jwst, green spiral galaxy`）。
> Repo [https://huggingface.co/dallinmackay/JWST-Deep-Space-diffusion](https://huggingface.co/dallinmackay/JWST-Deep-Space-diffusion)
**Web**
```text
https://huggingface.co/dallinmackay/JWST-Deep-Space-diffusion/resolve/main/JWST-Deep-Space.ckpt
```
### copeseethemaldchinai_10000.ckpt (samdoesart)
这是另一个基于Samdoesart作品的Dreambooth模型。
> 100 images
> No class images.
> 1e-6 learning rate.
> Sample guidance scale set to 9.5
> based on "chinai (anything)"
> Use `copeseethemald style` in prompt
>
> 100张图片
> 无分类图片。
> 1e-6的学习率。
> 样本指导尺度设置为9.5
> 基于“chinai(任何东西)”
> 在提示中使用`copeseethemald style`
**Torrent**
```text
magnet:?xt=urn:btih:4f1365b3dd30541d2c1becfd5d54160928916ba4&dn=copeseethemaldchinai_10000.ckpt&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337%2fannounce&tr=udp%3a%2f%2f9.rarbg.com%3a2810%2fannounce&tr=udp%3a%2f%2fopentracker.i2p.rocks%3a6969%2fannounce&tr=https%3a%2f%2fopentracker.i2p.rocks%3a443%2fannounce&tr=udp%3a%2f%2ftracker.torrent.eu.org%3a451%2fannounce&tr=udp%3a%2f%2fopen.stealth.si%3a80%2fannounce&tr=udp%3a%2f%2ftracker.tiny-vps.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.pomf.se%3a80%2fannounce&tr=udp%3a%2f%2ftracker.dler.org%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.altrosky.nl%3a6969%2fannounce&tr=udp%3a%2f%2fp4p.arenabg.com%3a1337%2fannounce&tr=udp%3a%2f%2fopen.demonii.com%3a1337%2fannounce&tr=udp%3a%2f%2fmovies.zsw.ca%3a6969%2fannounce&tr=udp%3a%2f%2fipv4.tracker.harry.lu%3a80%2fannounce&tr=udp%3a%2f%2ffe.dealclub.de%3a6969%2fannounce&tr=udp%3a%2f%2fexplodie.org%3a6969%2fannounce&tr=udp%3a%2f%2fexodus.desync.com%3a6969%2fannounce&tr=udp%3a%2f%2fbt1.archive.org%3a6969%2fannounce&tr=udp%3a%2f%2f6ahddutb1ucc3cp.ru%3a6969%2fannounce&tr=https%3a%2f%2ftracker.nanoha.org%3a443%2fannounce
```
**Web**
```text
https://mega.nz/file/xT9jVToK#Sj1S76kl-PC-zCRwJ2FWen6DS0NHY0IXFFAkXhm03eo
```
### CopeSeetheMald-berry200_20400.ckpt (samdoesart)
Another samdoesart dreambooth model.
> 204 images @ 20.4k steps
> 1e-6 learning rate
> based on "berry mix"
> Use `copeseethemald style` in prompt
**Torrent**
```text
magnet:?xt=urn:btih:e4f1f4b9d7d6cf8570914fe22318b44c18d6d602&dn=CopeSeetheMald-berry200_20400.ckpt&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337%2fannounce&tr=udp%3a%2f%2f9.rarbg.com%3a2810%2fannounce&tr=udp%3a%2f%2fopentracker.i2p.rocks%3a6969%2fannounce&tr=https%3a%2f%2fopentracker.i2p.rocks%3a443%2fannounce&tr=udp%3a%2f%2ftracker.torrent.eu.org%3a451%2fannounce&tr=udp%3a%2f%2fopen.stealth.si%3a80%2fannounce&tr=udp%3a%2f%2ftracker.tiny-vps.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.pomf.se%3a80%2fannounce&tr=udp%3a%2f%2ftracker.dler.org%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.altrosky.nl%3a6969%2fannounce&tr=udp%3a%2f%2fp4p.arenabg.com%3a1337%2fannounce&tr=udp%3a%2f%2fopen.demonii.com%3a1337%2fannounce&tr=udp%3a%2f%2fmovies.zsw.ca%3a6969%2fannounce&tr=udp%3a%2f%2fipv4.tracker.harry.lu%3a80%2fannounce&tr=udp%3a%2f%2ffe.dealclub.de%3a6969%2fannounce&tr=udp%3a%2f%2fexplodie.org%3a6969%2fannounce&tr=udp%3a%2f%2fexodus.desync.com%3a6969%2fannounce&tr=udp%3a%2f%2fbt1.archive.org%3a6969%2fannounce&tr=udp%3a%2f%2f6ahddutb1ucc3cp.ru%3a6969%2fannounce&tr=https%3a%2f%2ftracker.nanoha.org%3a443%2fannounce
```
**Web**
```text
https://mega.nz/folder/1a1xkQQK#4atlB1cJqI35InXxlxyA7A
```
### CopeSeetheMald-200_20400.ckpt (samdoesart)
Another samdoesart dreambooth model.
> 204 images @ 20.4k steps
> 1e-6 learning rate
> based on "blossom mix"
> Use `copeseethemald style` in prompt
**Torrent**
```text
magnet:?xt=urn:btih:9b92aeea5d136ddae25c0d6165405e6e4d144ff1&dn=CopeSeetheMald-200_20400.ckpt&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337%2fannounce&tr=udp%3a%2f%2f9.rarbg.com%3a2810%2fannounce&tr=udp%3a%2f%2fopentracker.i2p.rocks%3a6969%2fannounce&tr=https%3a%2f%2fopentracker.i2p.rocks%3a443%2fannounce&tr=udp%3a%2f%2ftracker.torrent.eu.org%3a451%2fannounce&tr=udp%3a%2f%2fopen.stealth.si%3a80%2fannounce&tr=udp%3a%2f%2ftracker.tiny-vps.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.pomf.se%3a80%2fannounce&tr=udp%3a%2f%2ftracker.dler.org%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.altrosky.nl%3a6969%2fannounce&tr=udp%3a%2f%2fp4p.arenabg.com%3a1337%2fannounce&tr=udp%3a%2f%2fopen.demonii.com%3a1337%2fannounce&tr=udp%3a%2f%2fmovies.zsw.ca%3a6969%2fannounce&tr=udp%3a%2f%2fipv4.tracker.harry.lu%3a80%2fannounce&tr=udp%3a%2f%2ffe.dealclub.de%3a6969%2fannounce&tr=udp%3a%2f%2fexplodie.org%3a6969%2fannounce&tr=udp%3a%2f%2fexodus.desync.com%3a6969%2fannounce&tr=udp%3a%2f%2fbt1.archive.org%3a6969%2fannounce&tr=udp%3a%2f%2f6ahddutb1ucc3cp.ru%3a6969%2fannounce&tr=https%3a%2f%2ftracker.nanoha.org%3a443%2fannounce
```
**Web**
```text
https://mega.nz/folder/ZG0UnRBJ#jykESWBUCr7hjOoNVTXwLw
```
### Black Souls bs_1500.ckpt
> A dreambooth trained on game cg from a game called black souls
> call for`bs` in the prompt
> have vae off, ensure clip skip is set to 1, and set cfg to a low number (like 6)
> Preview https://cdn.discordapp.com/attachments/1038283286046322819/1040125269761081444/grid-0000.png
**Torrent**
```text
magnet:?xt=urn:btih:63e9c043838f7bca078fb9607873957d11a88e24&dn=bs_1500.ckpt&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337%2fannounce&tr=udp%3a%2f%2f9.rarbg.com%3a2810%2fannounce&tr=udp%3a%2f%2fopentracker.i2p.rocks%3a6969%2fannounce&tr=https%3a%2f%2fopentracker.i2p.rocks%3a443%2fannounce&tr=udp%3a%2f%2ftracker.torrent.eu.org%3a451%2fannounce&tr=udp%3a%2f%2fopen.stealth.si%3a80%2fannounce&tr=udp%3a%2f%2ftracker.tiny-vps.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.pomf.se%3a80%2fannounce&tr=udp%3a%2f%2ftracker.dler.org%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.altrosky.nl%3a6969%2fannounce&tr=udp%3a%2f%2fp4p.arenabg.com%3a1337%2fannounce&tr=udp%3a%2f%2fopen.demonii.com%3a1337%2fannounce&tr=udp%3a%2f%2fmovies.zsw.ca%3a6969%2fannounce&tr=udp%3a%2f%2fipv4.tracker.harry.lu%3a80%2fannounce&tr=udp%3a%2f%2ffe.dealclub.de%3a6969%2fannounce&tr=udp%3a%2f%2fexplodie.org%3a6969%2fannounce&tr=udp%3a%2f%2fexodus.desync.com%3a6969%2fannounce&tr=udp%3a%2f%2fbt1.archive.org%3a6969%2fannounce&tr=udp%3a%2f%2f6ahddutb1ucc3cp.ru%3a6969%2fannounce&tr=https%3a%2f%2ftracker.nanoha.org%3a443%2fannounce
```
**Web**
```text
https://mega.nz/file/KkIgRY7a#VrKp_JwspTF4e05ApSy4hkJgGUcMKaXSbyB_COZ-o6k
```
### jaggy92500.ckpt
游戏截图.
> 这里是调用的术语：jaggy、ps_game_screenshot、pc_game_screenshot、gamecube_game_screenshot、blood_and_gore、intense_violence、zotov_game_screenshot、eroge_game_screenshot、life_sim_game_screenshot和/或alter_echo。这是按影响力降序排列的。还有一些其他的术语不足以命名，但有时会产生强烈的影响。我不会提到它们。您应该在否定提示中加入(cartoon)和可能的(menu)。预览图像：[https://imgur.com/a/J4i1DiN](https://imgur.com/a/J4i1DiN)
**Torrent**
```text
magnet:?xt=urn:btih:71847b56518e6d7d92dfe24e95f2ee474807b197&dn=jaggy92500.ckpt&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337%2fannounce&tr=udp%3a%2f%2f9.rarbg.com%3a2810%2fannounce&tr=udp%3a%2f%2fopentracker.i2p.rocks%3a6969%2fannounce&tr=udp%3a%2f%2fopen.stealth.si%3a80%2fannounce&tr=https%3a%2f%2fopentracker.i2p.rocks%3a443%2fannounce&tr=udp%3a%2f%2ftracker.torrent.eu.org%3a451%2fannounce&tr=http%3a%2f%2ftracker.openbittorrent.com%3a80%2fannounce&tr=udp%3a%2f%2ftracker1.bt.moack.co.kr%3a80%2fannounce&tr=udp%3a%2f%2ftracker.tiny-vps.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.moeking.me%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.dler.org%3a6969%2fannounce&tr=udp%3a%2f%2fp4p.arenabg.com%3a1337%2fannounce&tr=udp%3a%2f%2fopen.demonii.com%3a1337%2fannounce&tr=udp%3a%2f%2fmovies.zsw.ca%3a6969%2fannounce&tr=udp%3a%2f%2fipv4.tracker.harry.lu%3a80%2fannounce&tr=udp%3a%2f%2fexplodie.org%3a6969%2fannounce&tr=udp%3a%2f%2fexodus.desync.com%3a6969%2fannounce&tr=https%3a%2f%2ftracker.nanoha.org%3a443%2fannounce&tr=https%3a%2f%2ftracker.lilithraws.org%3a443%2fannounce&tr=https%3a%2f%2ftracker.cyber-hub.net%3a443%2fannounce
```
**Web**
```text
https://mega.nz/file/0SER2YpC#_MRc6p_sG9cSWqihpt33jpOWyMR8bCZrUaVkh4z5kGE
```
### ykgl.ckpt (y2k cgi girls)
> It does cgi girls from the y2k era. Trained for 40k steps.
> You call on them with `(ykgl cgi_girl)`, or `(ykgl cgi_girls)`, or just `(ykgl girl)`, and then maybe with , `cgi_artstyle`.
> Preview images https://imgur.com/a/r2aIcxo
**Web**
```text
https://mega.nz/file/hT0mgTqR#d8g133APl30UtDwsNmzV73_ZESi_kTa5pmQgJoxomn0
```
### CSRmodel (cutesexyrobutts)
Dreambooth model based on cutesexyrobutts art style.
Preview https://i.imgur.com/VPNUae8.png
**Torrent**
```text
magnet:?xt=urn:btih:46c46d2630043f9e47b0107b9680b5bd270263d7&dn=Systemy-CSRmodel.rar&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337%2fannounce&tr=udp%3a%2f%2f9.rarbg.com%3a2810%2fannounce&tr=udp%3a%2f%2fopentracker.i2p.rocks%3a6969%2fannounce&tr=udp%3a%2f%2fopen.stealth.si%3a80%2fannounce&tr=https%3a%2f%2fopentracker.i2p.rocks%3a443%2fannounce&tr=udp%3a%2f%2ftracker.torrent.eu.org%3a451%2fannounce&tr=http%3a%2f%2ftracker.openbittorrent.com%3a80%2fannounce&tr=udp%3a%2f%2ftracker1.bt.moack.co.kr%3a80%2fannounce&tr=udp%3a%2f%2ftracker.tiny-vps.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.moeking.me%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.dler.org%3a6969%2fannounce&tr=udp%3a%2f%2fp4p.arenabg.com%3a1337%2fannounce&tr=udp%3a%2f%2fopen.demonii.com%3a1337%2fannounce&tr=udp%3a%2f%2fmovies.zsw.ca%3a6969%2fannounce&tr=udp%3a%2f%2fipv4.tracker.harry.lu%3a80%2fannounce&tr=udp%3a%2f%2fexplodie.org%3a6969%2fannounce&tr=udp%3a%2f%2fexodus.desync.com%3a6969%2fannounce&tr=https%3a%2f%2ftracker.nanoha.org%3a443%2fannounce&tr=https%3a%2f%2ftracker.lilithraws.org%3a443%2fannounce&tr=https%3a%2f%2ftracker.cyber-hub.net%3a443%2fannounce
```
**Web**
```text
https://gofile.io/d/D1L69E
```
### Pepestyle
> A Dreambooth model created with the sole purpose of generating the rarest and dankest pepes.
> StableDiffusion 1.5 was used as a base for this model.
> 22 instance images, 400 class images, 2.2k steps at a 1.3e-6 learning rate.
> Use the phrase `pepestyle person`
> Repo https://huggingface.co/SpiteAnon/Pepestyle
**Web**
```text
https://huggingface.co/SpiteAnon/Pepestyle/resolve/main/pepestylev2_2200.ckpt
```
### dbmai
A dreambooth model from China.
Preview images https://imgur.com/a/fTDgBST
Info https://tieba.baidu.com/p/8136937175
**Torrent**
```text
magnet:?xt=urn:btih:89ede059b4f90887b1f1ce10ba7a37e1d8a0c4b5&dn=dbmai.ckpt&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337%2fannounce&tr=udp%3a%2f%2fopen.tracker.cl%3a1337%2fannounce&tr=udp%3a%2f%2ftracker.torrent.eu.org%3a451%2fannounce&tr=udp%3a%2f%2fopentracker.i2p.rocks%3a6969%2fannounce&tr=udp%3a%2f%2fopen.stealth.si%3a80%2fannounce&tr=udp%3a%2f%2f9.rarbg.com%3a2810%2fannounce&tr=https%3a%2f%2fopentracker.i2p.rocks%3a443%2fannounce&tr=http%3a%2f%2ftracker.openbittorrent.com%3a80%2fannounce&tr=udp%3a%2f%2ftracker.tiny-vps.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.moeking.me%3a6969%2fannounce&tr=udp%3a%2f%2fp4p.arenabg.com%3a1337%2fannounce&tr=udp%3a%2f%2fopen.demonii.com%3a1337%2fannounce&tr=udp%3a%2f%2fmovies.zsw.ca%3a6969%2fannounce&tr=udp%3a%2f%2fipv4.tracker.harry.lu%3a80%2fannounce&tr=udp%3a%2f%2fexplodie.org%3a6969%2fannounce&tr=udp%3a%2f%2fexodus.desync.com%3a6969%2fannounce&tr=https%3a%2f%2ftracker.nanoha.org%3a443%2fannounce&tr=https%3a%2f%2ftracker.lilithraws.org%3a443%2fannounce&tr=https%3a%2f%2ftracker.cyber-hub.net%3a443%2fannounce&tr=https%3a%2f%2ftr.burnabyhighstar.com%3a443%2fannounce
```
**Web**
```text
https://drive.google.com/drive/folders/1MUtM5MTXM35fid5TE3tUSKXAqPP7oysz
```
### gigachad-diffusion
> StableDiffusion v1.5 used. 20 instance images, 400 class images, 2.2k steps at a 1e-6 learning rate.
> Token `gigachad`
> Info & preview images: https://huggingface.co/SpiteAnon/gigachad-diffusion
**Web**
```text
https://huggingface.co/SpiteAnon/gigachad-diffusion/blob/main/gigachad_2000.ckpt
```
### Complex-Lineart
> Trained on around 100 images at 768x768 resolution.
> Use prompt: `ComplexLA style`
> Use resolution near 768x768, lower resolution works but quality will not be as good.
> Repo & preview images: https://huggingface.co/Conflictx/Complex-Lineart
**Web**
```text
https://huggingface.co/Conflictx/Complex-Lineart/resolve/main/ComplexLA%20Style.ckpt
```
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