Safety
Fizgig Krea 2 training features update
https://github.com/shootthesound/Fizgig Intelligent trainer - Per-image loss tracking with self-adapting training runs — every image gets its own verdict (easy / suspect / stuck / exhausted) and its o
https://github.com/shootthesound/Fizgig Intelligent trainer - Per-image loss tracking with self-adapting training runs — every image gets its own verdict (easy / suspect / stuck / exhausted) and its own learning rate - Auto-recaptioning: stuck images get their captions rewritten mid-run by Qwen3-VL from what's actually in the picture, then re-encoded and given a fresh start - Auto-exclusion of unfixable images — after two failed recaption attempts a genuinely bad image is dropped from the run entirely, with safety rails so healthy images can never be excluded - Problem Images window — live thumbnails, verdicts, and loss trends during training; edit a caption mid-run and it's picked up at the next epoch - Adaptive learning rate that moves in both directions — probes up when loss is descending cleanly, backs off and rolls weights back when things go unstable Dataset intelligence - Look Consistency Filter — ArcFace face-embedding scoring of every dataset image against 3 baselines, catching identity drift that loss curves can't see - Look-outlier warm-up — unusual-but-real images (profiles, tight angles) enter training gently at reduced LR and ramp up, instead of being punished or excluded Live feedback - Sample gallery with automatic likeness scoring — every preview scored against your dataset baselines on CPU while training runs, with a per-epoch trend chart and best-epoch highlight - Training Run Visualiser — scrub your whole run epoch-by-epoch per prompt, export as WebM Practical wins - Train the full 12.9B RAW model on modest cards — fp8 residency + auto block-swap tuned to your GPU (~14 GB resident) - Pause / Resume with zero quality loss — full optimizer, RNG, adaptive-LR and per-image-watch history restored, even across GUI restarts - Context LoRA — train a new LoRA on top of an existing frozen one so they coexist at inference (no other trainer does this) - Repair Studio — per-block sliders with live previews to fix an overbaked LoRA instead of retraining it - ComfyUI-compatible output, no conversion step submitted by /u/shootthesound [link] [comments]
Related
- [[tongyi-mai-papers-d-opsd-on-policy-self-distillation-for-con|[Tongyi-MAI Papers] D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models]]
- Improving Text-to-Image Generation with Intrinsic Self-Confidence Rewards
- How Fast Should a Model Commit to Supervision? Training Reasoning Models on the Tsallis Loss Continuum
Source: r/StableDiffusion | 2026-07-24