With v3 captions kept as-is and only the training amount pushed up to Anima's official 12,000+ step recommendation, the direction hit rate went 100% at ep150-180, crashed to 0% at ep200, then partially recovered to 67% at ep227 — a non-monotonic curve. 600-720 exposures per training image is the sweet spot; over 800 triggers catastrophic forgetting. Learning rate 2e-5, ~11 hours / $10 of RunPod training plus a sweet-spot epoch scan.
Alibaba ATH's video generation model HappyHorse-1.0: API test status on Model Studio, open weights availability, Mac local inference reality, and which GPU to pick on RunPod.
Took 53 cleaned images prepared for WAI-IL and trained a WAI-Anima character LoRA with AnimaLoraToolkit + RunPod. Training itself ran for $1.22, but at inference the side ponytail direction wouldn't shift with Danbooru tags or natural language. Verification record showing the issue is a directional bias inherited from Anima base (preview3-base onward).
I dropped the nervous sample identified as the culprit last time, plus 5 others, and retrained the LoRA under otherwise identical conditions. The sweat drops on ep08 angry are gone, and as a bonus, ep06 produced the closed-mouth restrained anger that the previous training never managed to reproduce.
Training an Illustrious-XL LoRA on RunPod for around $1 by doing env setup on a $0.08/hr CPU Pod and renting the 4090 only for actual training. Network Volumes attach to both pods at the same time, so there's no idle GPU billing. Four sd-scripts gotchas hit on the way included.
Testing See-through for anime character PSD decomposition: 23 generated layers, front/back hair separation, hidden-area inpainting, and what LayerDiff + Marigold actually produced from a single illustration.
Using tori29umai’s LoRA to automatically split facial parts, results from batching 28 images, and a log of running into the limits when attempting finer hair separation
Configuration for running a Qwen-Image-Layered LoRA that automatically separates facial parts on RunPod. Comparison of RTX 6000 Ada (48GB) and RTX PRO 6000 (96GB).
Hands-on RunPod log for Qwen-Image-Edit NSFW using Phr00t AIO: why my RTX 4090 attempt failed, what worked on RTX 5090, and how I used it to create 3-view reference sheets for a 3D model base mesh.
Setup notes for Qwen-Image-Edit-2511 on RunPod's RTX 4090 ($0.34/hr) using the ComfyUI template. Includes the fal Multiple-Angles LoRA (4 elevations × 8 azimuths × 3 distances) and a per-image cost breakdown that ends up cheaper than buying a 4090.
