Add h3lora/sidecars.py to peel adaln_basis, adaln_mean, and silu_t_emb_grid from checkpoint state dicts and stash them on model/patcher objects so ComfyUI doesn't drop them. Install a load_model_weights wrapper (ensure_load_hook) in __init__.py and call it from h3lora.apply; use sidecar collect when creating AdalnContext. Include unit tests (tests/test_sidecars.py) for peel/attach/collect and the wrapper. Also update README with no attribution by proxy. Thanks pl0x
Introduce auto-balance measurement and per-modality adaLN scaling for MiniMax H3.
- Add gain.py to measure LoRA perturbation (rel, factor) and cache results; expose measure_file/measure_state_dict.
- Add modality.py to scale adaLN rows by {video,text,audio} and describe/apply those changes.
- Add server route /h3_power_lora_stack/balance (h3lora/server.py) and register it in __init__.py to support the UI button.
- Integrate measurement and modality scaling into apply_stack and report LoRA rel/factor suggestions.
- Add H3AdalnModality node and adaln_modality input in nodes.py.
- Update web UI (web/h3_power_lora_stack.js) with auto-balance/restore buttons, server call, badges, and client-side behavior.
- Document features and rationale in README.md.
These changes keep measurements cached and never boost measured LoRAs (factor clamped ≤1).
Add a ComfyUI plugin implementing a stacked multi-LoRA loader for MiniMax H3. Introduces H3PowerLoraStack and H3LoraInspector node classes, plus modules: adaln (adaLN dense↔curve basis conversion), branch (runtime low-rank branches for quantized weights), apply (stack orchestration), detect (safetensors header introspection), keymap (key normalization), nodes, and a web UI (h3_power_lora_stack.js). Includes pyproject metadata and README. Preserves quantized kernels via branching, rebases adaLN pairs, handles many naming conventions, and provides a browser picker and per-LoRA reporting.
doggeddalle