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Please review the model introduction carefully before downloading the model
モデルをダウンロードする前に、モデル紹介をよく見てください
本系列模型及衍生模型,禁止上传LiblibAI或ShakkerAI
This series of models and their derivatives are prohibited from being uploaded to LiblibAI or ShakkerAI
このシリーズのモデルおよびその派生モデルは、LiblibAIまたはShakkerAIにアップロードすることは禁止されています
注意:
👇下面的Anything模型为冒用名称,并非本人制作,请不要进行付费
👇This Anything model is an unauthorized use of the name and was not created by me. Please do not make any payments.

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AI art should be looked like AI, not like humans.
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Anything-XL
AnythingXL β 4 is the AnythingXL here. If you download the previous model, there is no need to download it again.
AnythingXLbeta4 is another product encouraged by friends in the group. The premise is the highly developed SDXL model, with the quality of the trained model getting higher and higher. The negative hint word in the display graph's embedding name is only copied, and it actually has no effect. Beta4 was created because the model with the fourth test version was the only one I could tolerate looking at. Model fusion is a dead end, with a complete mess in terms of artistic style diversity and the accuracy of some prompt words.
Formula:
aingdiffusionXL_V0.6 x 0.144375
animagineXLV3 x 0.144375
cutecore_xl x 0.12375
kohakuXLDelta_rev1 x 0.1375
BAXLBArtstyleXLv2 x 0.3375
ponyV6 x 0.1125Model order only represents fusion order and has nothing to do with model quality
Model merge is implemented using the Webui-Supermerge plugin. According to FairAIPublicLicense1.0-SD, the recipe needs to be publicly disclosed, and any merged models that merged this model must also disclose the merge recipe in accordance with this license.
Parameters+:
Prompt words are different from SD1.5, and for best results, it is recommended to follow a structured prompt template:
<|special|>,
<|artist|>,
<|special(optional)|>,
<|characters name|>, <|copyrights|>,
<|quality|>, <|meta|>, <|rating|>,……
<|tags|>, special(optional):These prompt words only need to be typed once, put in the front, there is no need to put in the back
Special tags:
The model can still be used without these special cue words, but incorporating these special tags when necessary can help steer the generated results towards the desired direction.
years:
These words help guide the results towards modern and retro anime art styles, with a specific timeframe of approximately 2005 to 2023
newest 2021 to 2024
recent 2018 to 2020
mid 2015 to 2017
early 2011 to 2014
old 2005 to 2010NSFW:
These words help guide the results towards adult content, but generally do not generate adult content if rating words are not included.
Of course, you can also put it in negative prompts.
safe General
sensitive Sensitive
nsfw Questionable
explicit, nsfw Explicitquality:
While this model can function without quality words, in practice, these words can still be used to adjust the output.
masterpiece > 95%
best quality > ?
great quality > ?
good quality > ?
normal quality > ?
low quality > ?
worst quality ≤ 10%Resolution:
You are free to use the vast majority of reasonable resolutions, whether it is the resolution used by SD1.5 at 512*768 or higher resolutions above 2048, each will have a different effect. However, using images that are too large or too small may cause the picture to break down or the character/background structure to become distorted.
Tags:
If you want to generate high-quality pictures, you can use negative prompts, such as:
nsfw, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, artist nameNegative tags can include common negative tags, but it is best not to assign too high of a weight to their content, for example (ugly:2.8).
Because of models merge, some labels in the original model that have not been fully trained may be lost, and some labels may need to have a weight of over 1.5 in order to be effective.
Resolution:
A resolution greater than 1024×1024 is recommended, and hires fix is recommended if you want higher resolution or quality
Most of the generation parameters of the example graph are:
euler_a | 20steps | no hires fix | CFG72048 x 2048 not recommended
……
1280 x 2048
1280 x 1536
960 x 1536 Recommended
1024 x 1024 1:1 Square
……
960 x 640
768 x 512 SD1.5
……
2048 x 512 ¿ Unable to guarantee the quality
512 x 2048 ¿ Unable to guarantee the qualityDisclaimer:
All images generated by the model are created by the users themselves, and the model author cannot control the images generated by the users. The model author will not be held responsible for any potential copyright infringement or unsafe images.
License:
Anything now uses the Fair AI Public License 1.0-SD, compatible with Stable Diffusion models.All versions of the models in the Anything series are open source using this protocol. Key points:
Modification Sharing: If you modify Anything, you must share both your changes and the original license.
Source Code Accessibility: If your modified version is network-accessible, provide a way (like a download link) for others to get the source code. This applies to derived models too.
Distribution Terms: Any distribution must be under this license or another with similar rules.
Compliance: Non-compliance must be fixed within 30 days to avoid license termination, emphasizing transparency and adherence toopen-sourcevalues.
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您所看到的是单独给日本和中国AI玩家的备注:
①除非需要生成2048x2048以上的图或者遇到严重问题,否则请放弃高清修复。
②如果你感觉模型偏向某方面,请先检查提示词。一些提示词在之前使用的模型上可能无效,在这里可能有效。
③请不要用SD1.5的使用习惯来使用SDXL,因为两个模型本质上不同。如有必要,请使用简介中的质量词,而不是8k高清等。
④最好不要和NegativeXL一起使用,也不建议使用高权重的负面提示词,如(ugly:2)。
⑤想要一张好图片,请尽可能详细描述内容,而不要仅标注"1girl, nsfw",这样无法得到好的图片。
あなたが見ているのは、日本と中国のAIプレイヤーへの単独の備考です:
①2048x2048以上の画像を生成する必要があるか、深刻な問題が発生している場合を除き、高画質修復をやめてください。
②モデルが特定の側面に偏っている場合や他の問題がある場合は、ヒントワードを確認してください。一部のヒントワードは以前のモデルでは機能しないかもしれませんが、ここでは有効になる可能性があります。
③SD1.5の使用法ではなく、SDXLの使用法は異なるため、注意してください。必要な場合は、8kの高画質などではなく、以下に示す品質の言葉を使用してください。
④NegativeXLとの組み合わせは避けるべきであり、(ugly:2)のような大きなウェイトのネガティブなヒントワードの使用もおすすめしません。
⑤良い画像が必要な場合は、内容を可能な限り詳細に説明してください。単に「1girl, nsfw」というラベルを付けるだけでは良い画像が得られません。
Description
FAQ
Comments (44)
请问v5使用哪个vae
请问作者大大如何修复CLIP偏移呢?使用某个插件吗?
可以通过MBW(分权融合)插件修复偏移的Clip
请问作者这个模型对tag有很强的识别能力,用MBW是怎么实现的呢
作者你好,我刚开始学习训练模型,本来以为用ANYTING系列作为基础模型很方便,但看了你的说明貌似不妥。你是认为该用官方1.5模型重新喂图么?我想做一个干净的BD模型只喂特定的图,safetensors模型是不能用的是吧?
自己做一个干净的模型?你开什么玩笑,就用那3 5000张图,出来的结果只有僵死的绘画表现。初始模型就用了57亿张图,而且这数据量还过少了,怎么说也得扩大100倍,参考文本GPT的参数量
BV1Mm4y117Ci 你看一下这个视频,在B站bilibili搜索框输入 BV1Mm4y117Ci
嗯好的我去看看~我没有从新做个新模型的意思,我只是想基于官方模型做个相对纯粹点的模型而已- -,不merge不MIX。因为同质化太严重了。
@cyusyn2 感觉你的意思其实是要做Lora模型
感觉你说的像是个lora模型,用来添加在大模型上面获得更加稳定的效果用的,safetensors和checkpoints本质一个东西pytorch模型,但是checkpoints,ckpt没有安全措施,如果下到带恶意代码的模型,恶意代码会被执行,safetensor就字面意思上的“safe”了而已。
簡介太感人了,我看到一個工匠的堅持
Are AOM series well-mixed please? I pretty wants to know.
I have been using them for a long period. But recently I found problems that they don't follow my prompts well. Could it caused by bad-mix you referred?
请问 AOM系列是混合良好的吗,可能有点冒犯,但我真的很想知道。
我已经使用AOM系列很长一段时间了。但最近发现最新的AOM3有些时候并不遵循我的prompts,是不是正是因为他混合的很差,现在想换模型也不知道该用哪个……
AOM系列提示词并不准确
For some reason my generations seem to really not like drawing nipples. Some results before hires. fix might have areolaes drawn but after hires. fix they're just completely nude with no nipples drawn. Do you have to explicitly write 'nipples' in the prompts for this model to draw nipples in?
yeah thats kinda how i got that to work
大大~给我推荐一个画悬疑的MODLE可以吗?
什么停尸间、凶案现场、尸体
+1俺也想要
+2
插个眼
那需要的不应该是tag或者LORA吗?
Yuno, I just wanted to comment that I appreciate your efforts at translating the later release notes to English, even though you have to use translation software because you don't speak English.
Part of the reason I'm glad you translated it is:
I tried Anything v4.5 before I knew it was unofficial, in an AI game on Steam called "AI Roguelite". But Anything v4.5 has bad low saturation issues in that game, because apparently they used the wrong VAE or did something similarly wrong, like you explained in your notes.
So anyway, I just wanted to let you know the time you took to use machine translation wasn't wasted, because it helped me understand why I had issues when running the (unofficial) v4.5.
Also, I think you did a creative thing by skipping v4 and just releasing v5, since someone else already stole the v4 name. Probably better to just skip v4 and tell everyone "v4 is not mine and is unofficial" and avoid lots of confusion about names. So that seems to me like a bit of a creative "martial arts" sidestep, haha. Good work! :)
简介提示里的说明对我非常有用,多谢。
v5没有配套的vae吗,还是不需要vae。
V5 PR seems to break a lot with VAE checks.
"NansException: A tensor with all NaNs was produced in VAE."
If you disable the check you just end up with a Black Photo.
大佬,如果用v5做底模训练lora的话,应该使用最原始的版本吗还是哪个
用后缀最多的就行
@Yuno779 好的,谢谢!
@Yuno779 我又翻到了你最新的v2.1。v2.1适合还是v5更适合做底模训练啊,想炼炼2次元的lora试试
@lingxiang9875 想用哪个用哪个
v3 was absolutely awesome, but this model always produces horror if you use more than 10 prompts. other models can handle more than 10 prompts like a charme....
V3 is a simple draw card model and I don't like it(
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