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    CivitAI πŸ† Style Fusion - FFusionAI Entry (+dataset) - 5.1 3D Notebook 64dim ver
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    CivitAI Style FusionπŸ†LoRAs

    Last update: πŸš€ CivitAI Lora5 32DIM Notebook with dataset

    Last update: πŸš€ CivitAI Lora3 Configuration - Trained with CivitAI Trainer

    πŸš€ Date: 2023-11-10 | Title: CivitAI_64_ALL

    πŸ” Key Specifications:

    • Resolution: 1024x1024

    • Architecture: stable-diffusion-xl-v1-base/lora

    • Network Dim/Rank: 64.0, Alpha: 1.0

    • Module: networks.lora

    • Learning Rates: UNet LR & TE LR set to optimal levels

    • Optimizer: Advanced AdamW8bit

    • Epochs & Training: Intensive 10 epochs with 576 batches

    πŸ“Š Model Stats:

    • UNet Weight: Mag - 7.602, Str - 0.0187

    Resolution: 1024x1024 Architecture: stable-diffusion-xl-v1-base/lora
    Network Dim/Rank: 64.0 Alpha: 1.0
    Module: networks.lora
    Learning Rate (LR): 0.0005 UNet LR: 0.0005 TE LR: 5e-05
    Optimizer: bitsandbytes.optim.adamw.AdamW8bit(weight_decay=0.1)
    Scheduler: constant  Warmup steps: 0
    Epoch: 10 Batches per epoch: 576 Gradient accumulation steps: 1
    Train images: 2304 Regularization images: 0
    Multires noise iterations: 6.0 Multires noise discount: 0.3
    Min SNR gamma: 5.0 Zero terminal SNR: True Max grad norm: 1.0  Clip skip: 1
    Dataset dirs: 1
            [img] 576 images
    UNet weight average magnitude: 7.602270778898858
    UNet weight average strength: 0.018722912685324843
    Text Encoder (1) weight average magnitude: 2.7649271326702607
    Text Encoder (1) weight average strength: 0.009535635958680934
    Text Encoder (2) weight average magnitude: 2.6905091182810352
    Text Encoder (2) weight average strength: 0.007233532415344915

    Delve into FFusionAI's approach to AI-driven style synthesis with our newly released LoRA models. Each model has been developed using CivitAI's official trainer, ensuring precision and quality.

    πŸ› οΈ LoRA Model Overview:

    • LoRA 1 - Lite Version: Designed for quick testing, this model utilizes a small dataset for swift style generation, operating with a 32-dimension capacity.

    • LoRA 2 - Community Fusion: A robust model developed from over 500+ images, submitted by various users for the CivitAI contest. This iteration also features a 32-dimension capacity.

    • LoRA 3 - Enhanced Fidelity: Building upon LoRA 2, this model is further trained with higher dimensions, focusing on improving the overall image quality.

    • LoRA 4 - Comprehensive Style Mash: Our expansive dataset of 1400 images represents a confluence of all FFusionAI submissions. This model undergoes additional UNet training to refine and diversify the generated styles.

    1. FFusionAI Style Capture & Fusion Showdown LoRA

    🎨 Dataset and Training:

    Included within the package are curated collections accessible at CivitAI Collections. The training prompts have been crafted with BLIP-2, FLAN-T5-XL, and ViT-H-14.

    Please note, original prompts were not utilized for training. Instead, intentional modifications were made using blip2-flan-t5-xl & ViT-H-14/laion2b_s32b_b79k to adjust and enhance the training dataset, which can be reviewed here.

    πŸ”„ Further Information:

    For a detailed examination of the training datasets, parameters, and model specifications, professionals and enthusiasts are encouraged to explore the metadata provided within the collection.

    • LORA 2

      πŸš€ CivitAI Configuration Overview - 2023-11-10

    πŸš€ Trained with the Official CivitAI Trainer

    πŸ“… Date: 2023-11-10

    πŸ–ΌοΈ Title: CivitAI_ALL

    πŸ” Resolution: 1024x1024

    πŸ—οΈ Architecture: stable-diffusion-xl-v1-base/lora

    βš™οΈ Key Settings:

    • Network Dim/Rank: 32.0

    • Alpha: 1.0

    • Module: networks.lora

    • Learning Rates: UNet LR - 0.0005, TE LR - 5e-05

    • Optimizer: AdamW8bit (weight_decay=0.1)

    • Epochs & Batches: 10 epochs, 167 batches/epoch

    • Train Images: 576

    πŸ“Š Model Stats:

    • UNet Weight: Mag - 3.755, Str - 0.0135

    • Text Encoder (1): Mag - 1.833, Str - 0.0091

    • Text Encoder (2): Mag - 1.836, Str - 0.0071

    🏷️ Prominent Tags:

    • Fusion styles, Artgerm, Beeple

    • Dark fantasy, Official artwork, Pinup art

    • Digital illustration, Fantasy & Sci-fi

    • ...and over 4500 more!

    🌐 FFusion.ai Contact Information

    Proudly maintained by Source Code Bulgaria Ltd & Black Swan Technologies.

    • πŸ“§ For collaborations, inquiries, or support: [email protected]

    • 🌍 Locations: Sofia | Istanbul | London

    Connect with Us:

    Our Websites:

    Description

    Trained on Civitai Trainer only
    An attempt to expand the book image.

    https://civitai.com/images/3507510

    64dim
    ver + dataset

    { "unetLR": 0.0005, "clipSkip": 1, "loraType": "lora", "keepTokens": 0, "networkDim": 64, "numRepeats": 8, "resolution": 1024, "lrScheduler": "cosine_with_restarts", "minSnrGamma": 4, "targetSteps": 3840, "enableBucket": true, "networkAlpha": 1, "optimizerArgs": "weight_decay=0.1", "optimizerType": "AdamW8Bit", "textEncoderLR": 0.00005, "maxTrainEpochs": 10, "shuffleCaption": false, "trainBatchSize": 4, "flipAugmentation": false, "lrSchedulerNumCycles": 3 }

    FAQ

    LORA
    SDXL 1.0
    by idle

    Details

    Downloads
    386
    Platform
    CivitAI
    Platform Status
    Available
    Created
    11/17/2023
    Updated
    5/12/2026
    Deleted
    -
    Trigger Words:
    notebook
    book

    Files

    226663_training_data.zip

    Mirrors

    CivitAI (1 mirrors)

    Book_FFusion.safetensors

    Mirrors

    CivitAI (1 mirrors)