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    SECourses 3D Render for FLUX - Full Dataset and Workflow Shared - v1.0
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    Full Training Tutorial and Guide and Research For a FLUX Style

    Hugging Face repo with all full workflow, full research details, processes, conclusions, checkpoints,comparisons, prompts and more details > https://huggingface.co/MonsterMMORPG/3D-Cartoon-Style-FLUX

    Trigger word : ohwx 3d render

    Last image is training dataset as a grid

    This is a training of a public LoRA style (4 separate training each on 4x A6000).

    Experimenting captions vs non-captions. So we will see which yields best results for style training on FLUX.

    Generated captions with multi-GPU batch Joycaption app.

    I used my multi-GPU Joycaption APP (used 8x A6000 for ultra fast captioning)

    https://www.patreon.com/posts/110613301

    Joycaption examples

    I used my Gradio batch caption editor to edit some words and add activation token as ohwx 3d render

    https://www.patreon.com/posts/108992085

    Gradio batch caption editor

    The no caption dataset uses only ohwx 3d render as caption

    I am using my newest 4x_GPU_Rank_1_SLOW_Better_Quality.json on 4X A6000 GPU and train 500 epochs - 114 images

    https://www.patreon.com/posts/110879657

    Training configuration

    All trainings are saved as Float and 128 LoRA Network Rank thus they are above 2GB per checkpoint

    Inconsistent Dataset Training

    This is the first training I made with the below dataset

    Inconsistent-Training-Dataset-Images-Grid.jpg

    When you pay attention to the grid image above shared, you will see that the dataset is not consistent

    The training dataset with used captions (only for With Captions training) can be see in below directory

    Training-Dataset

    It has total 114 images

    This training total step count was 500 * 114 / 4 (4x GPU - batch size 1) = 14250 steps

    It took like 37 hours on 4x RTX A6000 GPU with slow config - faster config would take like half

    There were 2 trainings made with this dataset. Epoch 500 checkpoints are named as below

    SECourses_Style_Inconsistent_DATASET_NO_Captions.safetensors SECourses_Style_Inconsistent_DATASET_With_Captions.safetensors

    Their checkpoints are saved in below folders

    Training-Checkpoints-NO-Captions Training-Checkpoints-With-Captions

    Its grid results are shared below

    Inconsistent-Training-Dataset-Results-Grid-26100x23700px.jpg

    When you pay attention to above image you will see that it has inconsistent results

    Consistent Dataset Training

    After I noticed that the initial training dataset was inconsistent i have pruned the dataset and made it much more consistent

    Fixed-Consistent-Training-Dataset-Images-Grid.jpg

    When you pay attention to the grid image above shared, you will see that is way more consistent, still not perfect though

    Now it has total 66 images

    The training dataset with used captions for this training (only for With Captions training) can be see in below directory

    Fixed-Consistent-Training-Dataset

    This training total step count was 500 * 66 / 4 (4x GPU - batch size 1) = 8250 steps

    It took like 24 hours on 4x RTX A6000 GPU with slow config - faster config would take like half

    There were 2 trainings made with this dataset. Epoch 500 checkpoints are named as below

    SECourses_3D_Render_Style_Fixed_Dataset_NO_Captions.safetensors SECourses_3D_Render_Style_Fixed_Dataset_With_Captions.safetensors

    Their checkpoints are saved in below folders

    Training-Checkpoints-Fixed-DATASET-NO-Captions Training-Checkpoints-Fixed-DATASET-With-Captions

    Its grid results are shared below - this one includes results from inconsistent dataset as well

    Fixed-Consistent-Training-Dataset-Results-Grid-50700x15500px.jpg

    When you pay attention to above image you will see now it is way more consistent

    Best Checkpoint And Conclusion

    When inconsistent dataset was used, training with captions yielded way better results.

    However, when training made with a consistent dataset, no captions yielded better and more consistent results with early epochs.

    Thus I concluded that, epoch 75 of no-captions dataset is best checkpoint

    Here below comparison images for fixed dataset

    Fixed-Consistent-Training-Dataset-No-Captions-Only-Grid.jpg

    Fixed-Consistent-Training-Dataset-With-Captions-Only-Grid.jpg

    Best checkpoint download link : Training-Checkpoints-Fixed-DATASET-NO-Captions/SECourses_3D_Render_Style_Fixed_Dataset_NO_Captions-000075.safetensors

    75 checkpoints is equal to 75 * 66 / 4 = 1238 steps

    Tutorials To Train Your Style

    1 : https://youtu.be/bupRePUOA18

    FLUX: The First Ever Open Source txt2img Model Truly Beats Midjourney & Others - FLUX is Awaited SD3

    image

    2 : https://youtu.be/nySGu12Y05k

    FLUX LoRA Training Simplified: From Zero to Hero with Kohya SS GUI (8GB GPU, Windows) Tutorial Guide

    image

    3 : https://youtu.be/-uhL2nW7Ddw

    Blazing Fast & Ultra Cheap FLUX LoRA Training on Massed Compute & RunPod Tutorial - No GPU Required!

    image

    The dataset can't be used commercially

    Training progress

    Grid Testing Prompts - Example Images Picked From Grid - No Cherry Pick

    a ohwx 3d rendering of a car
    
    a car rendered in ohwx 3d style
    
    a ohwx style car image 
    
     a ohwx render of a car 
    
     a ohwx car 
    
     a ohwx 3d rendering of a chest, depicted in a cartoon style. The background is a plain white, making the chest and its contents stand out clearly. The overall style is playful and whimsical, with clean lines and bright colors, suggesting a fantasy or adventure theme. The illustration is highly detailed, with a focus on textures and shading to give the chest a realistic, three-dimensional appearance. The metal bands and rivets add a sense of realism and durability to the chest. The image is vibrant and eye-catching, inviting the viewer to imagine the treasure within. The illustration is likely used in a digital context, such as a game or a children's book. The colors are bright and bold, with a focus on oranges, browns, and golds to create a sense of warmth and excitement. The overall mood is one of excitement and discovery.
    
    a ohwx 3d rendering of an airplane, depicted in a cartoon style. The background is a plain white. The overall style is playful and whimsical, with clean lines and bright colors, suggesting a fantasy or adventure theme. The illustration is highly detailed, with a focus on textures and shading to give a realistic, three-dimensional appearance. The image is vibrant and eye-catching. The illustration is likely used in a digital context, such as a game or a children's book. The colors are bright and bold to create a sense of warmth and excitement.
    
    a ohwx 3d rendering of a battleship, depicted in a cartoon style. The background is a plain white. The overall style is playful and whimsical, with clean lines and bright colors, suggesting a fantasy or adventure theme. The illustration is highly detailed, with a focus on textures and shading to give a realistic, three-dimensional appearance. The image is vibrant and eye-catching. The illustration is likely used in a digital context, such as a game or a children's book. The colors are bright and bold to create a sense of warmth and excitement.
    
    a ohwx 3d rendering of a robot, depicted in a cartoon style. The background is a plain white. The overall style is playful and whimsical, with clean lines and bright colors, suggesting a fantasy or adventure theme. The illustration is highly detailed, with a focus on textures and shading to give a realistic, three-dimensional appearance. The image is vibrant and eye-catching. The illustration is likely used in a digital context, such as a game or a children's book. The colors are bright and bold to create a sense of warmth and excitement.
    
    a ohwx 3d rendering of a dog, depicted in a cartoon style. The background is a plain white. The overall style is playful and whimsical, with clean lines and bright colors, suggesting a fantasy or adventure theme. The illustration is highly detailed, with a focus on textures and shading to give a realistic, three-dimensional appearance. The image is vibrant and eye-catching. The illustration is likely used in a digital context, such as a game or a children's book. The colors are bright and bold to create a sense of warmth and excitement.
    
    a ohwx 3d rendering of a cat, depicted in a cartoon style. The background is a plain white. The overall style is playful and whimsical, with clean lines and bright colors, suggesting a fantasy or adventure theme. The illustration is highly detailed, with a focus on textures and shading to give a realistic, three-dimensional appearance. The image is vibrant and eye-catching. The illustration is likely used in a digital context, such as a game or a children's book. The colors are bright and bold to create a sense of warmth and excitement.
    
    a ohwx 3d rendering of an axe, depicted in a cartoon style. The background is a plain white. The overall style is playful and whimsical, with clean lines and bright colors, suggesting a fantasy or adventure theme. The illustration is highly detailed, with a focus on textures and shading to give a realistic, three-dimensional appearance. The image is vibrant and eye-catching. The illustration is likely used in a digital context, such as a game or a children's book. The colors are bright and bold to create a sense of warmth and excitement.
    
    a ohwx 3d rendering of a house, depicted in a cartoon style. The background is a plain white. The overall style is playful and whimsical, with clean lines and bright colors, suggesting a fantasy or adventure theme. The illustration is highly detailed, with a focus on textures and shading to give a realistic, three-dimensional appearance. The image is vibrant and eye-catching. The illustration is likely used in a digital context, such as a game or a children's book. The colors are bright and bold to create a sense of warmth and excitement.
    
    a ohwx 3d rendering of a dragon, depicted in a cartoon style. The background is a plain white. The overall style is playful and whimsical, with clean lines and bright colors, suggesting a fantasy or adventure theme. The illustration is highly detailed, with a focus on textures and shading to give a realistic, three-dimensional appearance. The image is vibrant and eye-catching. The illustration is likely used in a digital context, such as a game or a children's book. The colors are bright and bold to create a sense of warmth and excitement.
    
    a ohwx 3d rendering of a flower, depicted in a cartoon style. The background is a plain white. The overall style is playful and whimsical, with clean lines and bright colors, suggesting a fantasy or adventure theme. The illustration is highly detailed, with a focus on textures and shading to give a realistic, three-dimensional appearance. The image is vibrant and eye-catching. The illustration is likely used in a digital context, such as a game or a children's book. The colors are bright and bold to create a sense of warmth and excitement.
    
    a ohwx 3d rendering of a rose, depicted in a cartoon style. The background is a plain white. The overall style is playful and whimsical, with clean lines and bright colors, suggesting a fantasy or adventure theme. The illustration is highly detailed, with a focus on textures and shading to give a realistic, three-dimensional appearance. The image is vibrant and eye-catching. The illustration is likely used in a digital context, such as a game or a children's book. The colors are bright and bold to create a sense of warmth and excitement.
    
    a ohwx 3d rendering of a tank, depicted in a cartoon style. The background is a plain white. The overall style is playful and whimsical, with clean lines and bright colors, suggesting a fantasy or adventure theme. The illustration is highly detailed, with a focus on textures and shading to give a realistic, three-dimensional appearance. The image is vibrant and eye-catching. The illustration is likely used in a digital context, such as a game or a children's book. The colors are bright and bold to create a sense of warmth and excitement.
    
    a ohwx 3d rendering of a computer, depicted in a cartoon style. The background is a plain white. The overall style is playful and whimsical, with clean lines and bright colors, suggesting a fantasy or adventure theme. The illustration is highly detailed, with a focus on textures and shading to give a realistic, three-dimensional appearance. The image is vibrant and eye-catching. The illustration is likely used in a digital context, such as a game or a children's book. The colors are bright and bold to create a sense of warmth and excitement.
    
    a ohwx 3d rendering of a graphics processing unit (gpu), depicted in a cartoon style. The background is a plain white. The overall style is playful and whimsical, with clean lines and bright colors, suggesting a fantasy or adventure theme. The illustration is highly detailed, with a focus on textures and shading to give a realistic, three-dimensional appearance. The image is vibrant and eye-catching. The illustration is likely used in a digital context, such as a game or a children's book. The colors are bright and bold to create a sense of warmth and excitement.
    
    a ohwx 3d rendering of a fork, depicted in a cartoon style. The background is a plain white. The overall style is playful and whimsical, with clean lines and bright colors, suggesting a fantasy or adventure theme. The illustration is highly detailed, with a focus on textures and shading to give a realistic, three-dimensional appearance. The image is vibrant and eye-catching. The illustration is likely used in a digital context, such as a game or a children's book. The colors are bright and bold to create a sense of warmth and excitement.
    
    a ohwx 3d rendering of a lock, depicted in a cartoon style. The background is a plain white. The overall style is playful and whimsical, with clean lines and bright colors, suggesting a fantasy or adventure theme. The illustration is highly detailed, with a focus on textures and shading to give a realistic, three-dimensional appearance. The image is vibrant and eye-catching. The illustration is likely used in a digital context, such as a game or a children's book. The colors are bright and bold to create a sense of warmth and excitement.
    
    a ohwx 3d rendering of a umbrella, depicted in a cartoon style. The background is a plain white. The overall style is playful and whimsical, with clean lines and bright colors, suggesting a fantasy or adventure theme. The illustration is highly detailed, with a focus on textures and shading to give a realistic, three-dimensional appearance. The image is vibrant and eye-catching. The illustration is likely used in a digital context, such as a game or a children's book. The colors are bright and bold to create a sense of warmth and excitement.
    

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    Comments (20)

    nicccSep 8, 2024· 14 reactions
    CivitAI

    Pal... who the fuk is going to train for 37 hours ? Are you autistic ? You cant be real with this.This style does not need that many pics, its just 3d render.Some of your stuff is useful but this is insanity.

    SECourses
    Author
    Sep 8, 2024· 7 reactions

    niccc please read the article without skipping a word and reply a comment again. you will understand purpose of this LoRA

    SouthbayJaySep 8, 2024· 11 reactions

    Bro chill the flux out! The man is doing RESEARCH, he doesn't just watch YT videos and follows the pack, he tests shit on his own to find out what works.. People like him is the reason why a lot of us know what works and what doesn't.. He's simply sharing his results which he posts for free!

    gurilagardnrSep 8, 2024· 3 reactions

    I regularly train large finetuned models that can take up to 80 hours on a single gpu. There are treatments available for ADHD.

    SeBL4RDOct 24, 2024· 1 reaction

    @SouthbayJay “research” loul, he's just a wanker with a big graphics card looking to make a buck.

    He's learned nothing more than the others.

    LDWorksDavidSep 8, 2024· 11 reactions
    CivitAI

    Honestly. You, me and anyone can get this with just 32 dimensions -or even lower as 16 (same alpha)-, less number of images on dataset )if you want) and of course... what bothers me... do you really need to train this on MULTI GPU? On RTX A6000's? This is a mistake and a bad follow up for people starting to train. It's just an opinion though.

    SECourses
    Author
    Sep 8, 2024· 6 reactions

    multi gpu totally depends on how much longer you want to wait, how many images you have. if you read the article you will notice that i picked 75 epoch as best. it would be 75 * 66 = 4950 steps which is totally doable on a single GPU

    LDWorksDavidSep 8, 2024· 4 reactions

    @SECourses Yeah! of course I readed it but you should point (as this is a some sort of a guide) that this is also doable on consumer GPU's (taking more time, yup) and not looking like you need to rent to train. I already know that as I also know that you don't need 128 dimensions or caption 3d render when the target style is the same style, but we shouldn't assume everyone should know this or know this. Take this as a friendly advice and not an attack U^^.

    SECourses
    Author
    Sep 8, 2024· 5 reactions

    @LDWorksDavid well that is why watching tutorials is super important because i explain everything you just said in video :)

    SouthbayJaySep 8, 2024· 11 reactions
    CivitAI

    Amazing work thank you for all the info! Don't listen to the haters, the AI world needs people like yourself that put in the actual work, research every angle and thankfully you openly share the outcome. I appreciate you!!! Keep up the good work!!

    SECourses
    Author
    Sep 8, 2024· 2 reactions

    thank you so much

    renderartistSep 8, 2024· 5 reactions
    CivitAI

    Thanks for sharing your experiences, the style looks pretty amazing and I'll use it despite the huge size because of that. I'm curious to see if you can optimize this some more.

    SECourses
    Author
    Sep 8, 2024· 1 reaction

    awesome thank you so much for the comment

    DragoySep 12, 2024· 1 reaction

    Try Lora's resize tool in kohya_ss

    SECourses
    Author
    Sep 13, 2024· 1 reaction

    @Dragoy nice to know

    SECourses
    Author
    Sep 13, 2024· 2 reactions

    @Dragoy i am gonna test and upload now 

    ogkai_1111Sep 8, 2024· 2 reactions
    CivitAI

    This is a great resource. Thank you a lot. 5K steps is pretty normal for full training a dataset. Very easily can be done in one night on Rtx 4090.

    SECourses
    Author
    Sep 8, 2024· 1 reaction

    100% you can do easily in few hours. thank you so much for the comment

    tdfilmstudioSep 8, 2024· 3 reactions
    CivitAI

    Thank you for your Wonderful work. Really happy to see your custom Lora and findings on Civit AI. Go for hundred more! The sky is the limit

    SECourses
    Author
    Sep 8, 2024· 1 reaction

    thank you so much. yes i have bigger lora and fine tuning plans hopefully

    LORA
    Flux.1 D

    Details

    Downloads
    452
    Platform
    CivitAI
    Platform Status
    Available
    Created
    9/7/2024
    Updated
    5/14/2026
    Deleted
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    Trigger Words:
    ohwx 3d render

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    Available On (1 platform)

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