類型
LORA
发布時間
2023-10-31
基础模型
SDXL 1.0
版本介绍
Week 3 Style from HOT MJ category
详情
推薦
Week 3: "HOT"- LoRA
Week 3: "ALLin"- LoRA
FF-Midj-Top-v0565
Week 2: "RISING"- LoRA
Week 2: "TOP"- LoRA
Week 2: "HOT"- LoRA
FF-Top-LoRA-FA-TX-Encoder
Week 3: "NEW"- LoRA
Week 3: "RISING"- LoRA
MidJ Last 500 - CivitAI
MidJ Last 500 - LoRA
Week 2: "NEW"- LoRA
FF-Midj-Rise-v0564
831
39
370
Weekly MidJourney Style Experiment: Last 500 Images
Update (11/02/23) : adding WEEK 3 FFUsion (ALL IN) LoRA of Hot, Rising, and New
🗓 Current Week's Exploration (10.31.23): This week LoRAs are fine-tuned for the
🏆'Style Capture & Fusion Showdown' (rejected entry)
Week 3 Styles of Hot, Rising, and New MJ categories: 10.31.23
🔥 Previous Week’s LoRAs (10.23.23):
last week styles from the 'Hot', 'Rising', and 'New' category
A recent experiment conducted using the last 500 images from the 'MidJourney' categories: Hot, Rising, and New.
Data Acquisition and Integrity:
All images were sourced responsibly, with no use of unofficial tools for acquisition.
The images were obtained using the sanctioned Corporate/Enterprise account.
Technical Overview:
The images were processed using the
ViT-L-14/openaimodel (quick sloppy run). For testing, theprodigytool was employed.It's important to note that the current quality of results does not align with our typical production standards. However, for those interested in further details, a training set from the official Civitai trainer is available.
The experiment utilized the capabilities of the Civitai trainer(default out of the box configuration)
09/26/2023 03:48:12 AM
SUBMITTED
09/26/2023 03:48:40 AM
PROCESSING
09/26/2023 05:21:46 AM
READY
Lora FA text encoder, and the Kohya tools, all operating on the H100 80GB.
We appreciate your continued interest and support. Further updates will be provided as the experiment progresses.
Each one took 20-30min
📂 MidJ_Last_500_-_Experiment.safetensors
📅 Date:
2023-09-26T02:20:38🏷️ Title:
MidJ_Last_500_-_Experiment🖼️ Resolution:
1024x1024🧪 Architecture:
stable-diffusion-xl-v1-base/lora🌐 Network Dimensions:
Dim/Rank:
32.0Alpha:
16.0
🔌 Module:
networks.lora🔧 Configurations:
Learning Rate:
0.0005UNet LR:
0.0005TE LR:
5e-05Optimizer:
bitsandbytes.optim.adamw.AdamW8bit(weight_decay=0.1)Scheduler:
cosine_with_restartsWarmup Steps:
0Epochs:
10Batches per Epoch:
128Gradient Accumulation Steps:
1Train Images:
500Regularization Images:
0Multires Noise Iterations:
6.0Multires Noise Discount:
0.3Min SNR Gamma:
5.0Zero Terminal SNR:
TrueMax Gradient Norm:
1.0Clip Skip:
1Dataset Directories:
1Image Count:
500 images
📈 Stats:
UNet Weight (Avg. Magnitude):
3.0170UNet Weight (Avg. Strength):
0.0111Text Encoder (1) - Weight (Avg. Magnitude):
1.7304Text Encoder (1) - Weight (Avg. Strength):
0.0087Text Encoder (2) - Weight (Avg. Magnitude):
1.7614Text Encoder (2) - Weight (Avg. Strength):
0.0068
📂 FF-Midj-Last-v0563.safetensors
📅 Date:
2023-09-26T01:16:09🏷️ Title:
FF-Midj-Last-v0563🖼️ Resolution:
1024x1024🧪 Architecture:
stable-diffusion-xl-v1-base/lora🌐 Network Dimensions:
Dim/Rank:
64.0Alpha:
32.0
🔌 Module:
networks.lora📈 Stats:
UNet Weight (Avg. Magnitude):
2.6731UNet Weight (Avg. Strength):
0.0076Text Encoder (1) - Weight (Avg. Magnitude):
2.5809Text Encoder (1) - Weight (Avg. Strength):
0.0091Text Encoder (2) - Weight (Avg. Magnitude):
2.6613Text Encoder (2) - Weight (Avg. Strength):
0.0072
📂 FF-Midj-Rise-v0564.safetensors
📅 Date:
2023-09-26T02:01:20🏷️ Title:
FF-Midj-Rise-v0564🖼️ Resolution:
1024x1024🧪 Architecture:
stable-diffusion-xl-v1-base/lora🌐 Network Dimensions:
Dim/Rank:
64.0Alpha:
32.0
🔌 Module:
networks.lora📈 Stats:
UNet Weight (Avg. Magnitude):
2.6016UNet Weight (Avg. Strength):
0.0074Text Encoder (1) - Weight (Avg. Magnitude):
2.5694Text Encoder (1) - Weight (Avg. Strength):
0.0091Text Encoder (2) - Weight (Avg. Magnitude):
2.6260Text Encoder (2) - Weight (Avg. Strength):
0.0071
📂 FF-Midj-Top-v0564-FA-TX.safetensors
📅 Date:
2023-09-26T03:21:49🏷️ Title:
FF-Midj-Top-v0564-FA-TX🖼️ Resolution:
1024x1024🧪 Architecture:
stable-diffusion-xl-v1-base/lora🌐 Network Dimensions:
Dim/Rank:
64.0Alpha:
64.0
🔌 Module:
networks.lora_fa📈 Stats:
Text Encoder (1) - Weight (Avg. Magnitude):
5.8341Text Encoder (1) - Weight (Avg. Strength):
0.0191Text Encoder (2) - Weight (Avg. Magnitude):
6.0269Text Encoder (2) - Weight (Avg. Strength):
0.0153
⚠️ Note: No UNet found in this LoRA.
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