Add ETA to every training log line + epoch summary

Fix: fast VAE encoding (bs=64), auto-limit large datasets, ~5x faster caching"

Notebook: auto batch size, gradient checkpointing, no more OOM

Add gradient checkpointing + auto batch size to prevent OOM on T4

Add gradient checkpointing + zigzag index caching

Fix notebook: use pure-parquet datasets only, cartoon default

Fix dataset: drop broken keremberke, use pure-parquet datasets only (cartoon default, Artificio/WikiArt for styles)"

Fix: add trust_remote_code=True for datasets with legacy loading scripts

Fix notebook: use open SDXL VAE (no auth), 4ch latents, correct scaling

Fix VAE: switch to madebyollin/sdxl-vae-fp16-fix (open, no auth needed, 4ch latent)

Update README with Colab-optimized training workflow and dataset presets

Update notebook: latent pre-caching + small dataset presets for Colab

Add optimized training v2 with latent pre-caching for Colab

Fix: SDXL VAE (no login) + streaming dataset in notebook

Fix: SDXL VAE (no login), streaming dataset, step-based training

Fix: use SDXL VAE (4ch, no login needed)

Fix: streaming dataset in notebook (no full download on Colab)

Fix: streaming dataset (no full download), step-based training loop

Add Colab training notebook

Add training pipeline

Add model architecture

Add README with architecture docs and usage guide

initial commit