fa2cb600ee
Extends diffusion LoRA training beyond SDXL to the three popular DiT families via a single shared flow-matching loop parameterised by small per-family specs (loading, prompt/latent encoding, transformer forward, save). Verified against diffusers 0.38.0: - FLUX.1-dev: 2x2 latent packing + image ids, guidance-embed forward, on-the-fly nf4 QLoRA of the 12B transformer (the dev repo is gated, so training needs the user's HF token). - Qwen-Image: 5D VAE latents normalised by the per-channel latents_mean/std, img_shapes forward, prequant nf4 base by default (on-the-fly nf4 for the bf16 base). - Z-Image: list I/O with the reversed timestep convention and a negated prediction, bf16 only. The registry (get_trainer) and DiffusionFamily.trainable / train_base_repos now route these families to the DiT trainer; the SDXL blocklist guard is replaced by a positive family resolution that also rejects GGUF repos (inference-only) and still-unsupported families. Per-family defaults + labels + VRAM notes are exposed via family_train_infos for the Train UI. Memory: caption embeddings are precomputed once and the text encoders freed before the loop; gradient checkpointing (non-reentrant, required for bnb 4-bit) and 8-bit AdamW are on by default. |
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| .. | ||
| assets | ||
| auth | ||
| core | ||
| hub | ||
| loggers | ||
| models | ||
| plugins | ||
| requirements | ||
| routes | ||
| state | ||
| storage | ||
| tests | ||
| utils | ||
| __init__.py | ||
| _platform_compat.py | ||
| cloudflare_tunnel.py | ||
| colab.py | ||
| main.py | ||
| run.py | ||
| startup_banner.py | ||