
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:
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Resolution: 1024x1024
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Architecture: stable-diffusion-xl-v1-base/lora
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Network Dim/Rank: 64.0, Alpha: 1.0
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Module: networks.lora
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Learning Rates: UNet LR & TE LR set to optimal levels
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Optimizer: Advanced AdamW8bit
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Epochs & Training: Intensive 10 epochs with 576 batches
? Model Stats:
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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:
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LoRA 1 - Lite Version: Designed for quick testing, this model utilizes a small dataset for swift style generation, operating with a 32-dimension capacity.
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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.
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LoRA 3 - Enhanced Fidelity: Building upon LoRA 2, this model is further trained with higher dimensions, focusing on improving the overall image quality.
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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.
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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:
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Network Dim/Rank: 32.0
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Alpha: 1.0
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Module: networks.lora
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Learning Rates: UNet LR - 0.0005, TE LR - 5e-05
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Optimizer: AdamW8bit (weight_decay=0.1)
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Epochs & Batches: 10 epochs, 167 batches/epoch
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Train Images: 576
? Model Stats:
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UNet Weight: Mag - 3.755, Str - 0.0135
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Text Encoder (1): Mag - 1.833, Str - 0.0091
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Text Encoder (2): Mag - 1.836, Str - 0.0071
?️ Prominent Tags:
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Fusion styles, Artgerm, Beeple
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Dark fantasy, Official artwork, Pinup art
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Digital illustration, Fantasy & Sci-fi
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...and over 4500 more!
? FFusion.ai Contact Information
Proudly maintained by Source Code Bulgaria Ltd & Black Swan Technologies.
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? For collaborations, inquiries, or support: [email protected]
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? 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
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Tags
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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...
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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