AkashicPulse EQVAE is a model based on AkashicPulse series, but fine-tuned to utilize Anzhc's EQVAE as its VAE. (In theory,) This improve the model generation color and accuracy.
Recommended settings [UPDATED FOR V1.0.x]:
Same like v0.2, the model is in between needing RescaleCFG and not needing it. Expect to turn on and off this a lot.
The usage of artist tags IS HIGHLY RECOMMENDED. Put it at the FRONT of your prompt (and use BREAK if your generation platform support it).
Steps: 32-50
CFG: 7-10 with RescaleCFG on or off, or 4.5-6 if you don't wanna touch RescaleCFG
RescaleCFG: 0.7 OR OFF, inspect generated image quality if something is off.
Sampler: Euler a (or try AkashicSolver available on Adept Sampler with AkashicAOS).
Noise Scale: 0.9, using 1.0 will cause the model to over-generate noise.
Recommended negative prompt:
worst quality, low quality, bad anatomy, bad hands, text, signature, watermark, username, artist name, [things you want to remove]WARNING: Using excessive negative prompt might resulting the model to lose its quality.
Model Specs:
v1.0.2
Based on: AkashicPulse EQVAE v1.0.1-Base
Dataset size: ~21k
Epoch posted: Epoch 10 out of 10
EQVAE used: Anzhc's EQVAE B7
v1.0-v1.0.1
Based on: AkashicPulse EQVAE v0.2
Dataset size: ~4.6k
Epoch posted: Epoch 15 out of 15
EQVAE used: Anzhc's EQVAE B7
v0.2 [CHECK ABOUT THIS VERSION FOR DETAILS]
Based on: AkashicPulse EQVAE v0.1
Dataset size: ~9.4k
Epoch posted: Epoch 7 out of 10.
EQVAE used: Anzhc's EQVAE B7
v0.1
Based on: AkashicPulse 4.1
Dataset size: 10.6k, repeated twice.
Epoch posted: Epoch 9 out of 10.
EQVAE used: Anzhc's EQVAE B7
Description
First attempt at adding knowledge to the model, with 32 hours of wall clock training time.
Using v1.0.1-Base as base.
Dataset used:
hololive, 21k images from May 1st, 2025 until March 12th, 2026
Donation goal and 5-day early access is purely to support next batch of training. I hope you understand that GPU training time aren't free and I have limited budget for training.