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    BeautyFool Reality - v3.0
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    For v.4.0: This time I trained my model with many more images (1887 to be exact). It is a pruned model. It doesn't require vae but you can use it if you want. Clip skip was trained with 1, but it gives successful results with 2 as well. (I recommend using negative embeddings to avoid burning so you can get great results)

    For v.3.0: Let me describe what I did. I don't speak English, I hope I can explain. All my previous versions were merged models. In this model, I trained three different models with three different folders containing 188 photos, each image having 150 steps (epoch). The photos in the three folders were also different from each other. I couldn't decide which model was the most successful. All three gave very good results. So I finally combined these three models and published them as a single model. So it went through merging first, then training, then merging again. But the most time-consuming and tiring part was the training part. Since I did not have the opportunity to choose both options, I chose this option to emphasize that it has undergone training.

    -*- Let me give you a tip... A model tends to whatever style it was last trained with. You can test it as follows: generate 10-15 times with default settings (20 steps, 7 scale and 512x512 resolution (for 1.5 models)) without writing any negative or positive prompts. (If you want to make the images look clearer, you can write negative prompts provided that you do not use negative embedding). Whichever type of results you got the most in this test, it means that the trend of the model is in that direction -*-

    For v1.0: Like my previous anime model, this one consists of several models mixed with each other in certain proportions. I give the list of the mixture below, but I will not specify the mixing ratios. I would like to thank those who created these models.

    Absolute Reality

    Realistic Vision

    CyberRealistic

    Pirsus Epic Realism

    Ideal for creating ultra-realistic images. Some words can force the model to run nsfw. When the resolution is increased with Hires fix, it creates magnificent visuals. You may have problems with faces in smaller size images. In such cases, you can use adetailer applications such as almostiler.

    No need to use vae.

    I recommend increasing the resolution by using hires fix instead of using restore faces.

    It will continue to be developed.

    Description

    This is my first training attempt... I trained my model with more than 500 photos. The photographs I used were mostly portraits of beautiful women that I chose myself. I've seen it do quite well on models with red hair and freckles. I would appreciate if you share your experiences so that I can improve it further.

    -place the yaml file next to the model file-

    I am sharing the photo package I used for training with you. Those who want can create their own experience by downloading it: link

    FAQ

    Comments (5)

    ProseccoSpritzAug 13, 2023· 12 reactions
    CivitAI

    This model is misplaced: it's a MERGED model, not a TRAINED model!

    53rt5355iz
    Author
    Aug 13, 2023· 6 reactions

    Well, let me describe what I did. I don't speak English, I hope I can explain. All my previous versions were merged models. In this model, I trained three different models with three different folders containing 188 photos, each image having 150 steps (epoch). The photos in the three folders were also different from each other. I couldn't decide which model was the most successful. All three gave very good results. So I finally combined these three models and published them as a single model. So it went through merging first, then training, then merging again. But the most time-consuming and tiring part was the training part. Since I did not have the opportunity to choose both options, I chose this option to emphasize that it has undergone training.

    HarmilAug 13, 2023

    @53rt5355iz You should definitely put that info in the description. From the current description this sounds like a mix that was mislabeled.

    94655Aug 13, 2023· 6 reactions

    And the award for best hair-splitter on CivitAI goes to... @ProseccoSpritz

    7727Aug 14, 2023

    Merging cant still be involved and considered 'trained' if a original new trained dataset is included in the merge

    Checkpoint
    SD 1.5

    Details

    Downloads
    2,909
    Platform
    CivitAI
    Platform Status
    Available
    Created
    8/12/2023
    Updated
    5/13/2026
    Deleted
    -

    Files

    beautyfoolReality_v30.safetensors

    Mirrors

    beautyfoolReality_v30.yaml

    Mirrors

    CivitAI (87 mirrors)

    Available On (1 platform)

    Same model published on other platforms. May have additional downloads or version variants.