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SimpleTuner/minimaxmusic-reggae-test-lora-comfyui-v1-4k
minimaxmusic-reggae-test-lora-comfyui-v1-4k is a machine learning model from SimpleTuner. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Key-converted version of bghira/minimax-music-suno-reggae-rank128 (checkpoint-4000/pytorchloraweights.safetensors) for direct use with ComfyUI's native MiniMax Music3 LoRA loading.
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Updated Aug 15, 2026
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From the Hugging Face model README
Key-converted version of bghira/minimax-music-suno-reggae-rank128 (checkpoint-4000/pytorch_lora_weights.safetensors) for direct use with ComfyUI's native MiniMax Music3 LoRA loading.
The source checkpoint is a diffusers/PEFT-format LoRA with separate to_q/to_k/to_v/to_out.0 projections. ComfyUI's MiniMaxMusic3DiT attention module (comfy/ldm/minimax_music/dit.py) uses a single fused to_qkv Linear instead, and comfy/lora.py has no diffusers-format key mapping or QKV-splitting logic for this architecture — so the original file's keys never match and none of the LoRA loads.
This file renames/restructures the weights to ComfyUI's native key scheme:
to_out.0.lora_A/B.weight → diffusion_model.diffusion_transformer.transformer.layers.{i}.self_attn.to_out.lora_A/B.weight (direct copy, shapes already match)to_q/to_k/to_v LoRAs are fused into a single ...self_attn.to_qkv.lora_A/B.weight pair matching the target module's combined QKV Linear (out_features = dim * 3). This uses a block-diagonal construction on lora_B (row-stacked lora_A, block-diagonal lora_B) so the merged low-rank update reproduces each of the original per-branch B_q @ A_q, B_k @ A_k, B_v @ A_v deltas exactly in the corresponding q/k/v output rows — verified numerically against the source weights (max abs error 0.0 in bf16).Single flat .safetensors file, no diffusers-style subdirectories — drop it in ComfyUI/models/loras/ and use it with ComfyUI's LoraLoaderModelOnly/LoraLoader node against a MiniMax Music3 model.