CivitAI ? Style Fusion - FFusionAI Entry (+dataset)版本3. All Entries 64DIM LoRa (ID: 221353)

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)版本3. All Entries 64DIM LoRa (ID: 221353)

CivitAI Style Fusion?LoRAs

Last update: ? CivitAI Lora5 32DIM Notebook with dataset

Last update: ? CivitAI Lora3 Configuration - Trained with CivitAI Trainer

? Date: 2023-11-10 | Title: CivitAI_64_ALL

? 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

? 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
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.

?️ 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.

? 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

    ? CivitAI Configuration Overview - 2023-11-10

? Trained with the Official CivitAI Trainer

? Date: 2023-11-10

?️ Title: CivitAI_ALL

? Resolution: 1024x1024

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

⚙️ 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

? 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.

  • ? For collaborations, inquiries, or support: [email protected]

  • ? Locations: Sofia | Istanbul | London

Connect with Us:

Our Websites:

描述:

? CivitAI Lora3 Configuration - Trained with CivitAI Trainer

? Date: 2023-11-10 | Title: CivitAI_64_ALL

? 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

? Model Stats:

  • UNet Weight: Mag - 7.602, Str - 0.0187

Dataset dirs: 1

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

----------------------

Tags

----------------------

civitai fusion style 576

martin ansin 30

artgerm julie bell beeple 27

dramatic artwork 23

beeple and jeremiah ketner 22

official artwork 20

jen bartel 20

martin ansin artwork portrait 19

dark fantasy style art 17

greg beeple 17

pinup 16

pinup art 16

beautiful digital artwork 15

symmetrical epic fantasy art 14

stunning digital illustration 13

gorgeous digital art 13

neoartcore and charlie bowater 13

cyborg goddess in cosmos 13

beautiful retro art 13

fantasy art style 12

epic fantasy sci fi illustration 12

4562 more tags...

----------------------

训练词语: civitai fusion style

名称: CivitAI_64_ALL.safetensors

大小 (KB): 446066

类型: Model

Pickle 扫描结果: Success

Pickle 扫描信息: No Pickle imports

病毒扫描结果: Success

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)

CivitAI ? Style Fusion - FFusionAI Entry (+dataset)

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