MiniMax-H3 4-Step LoRA (FlashGen)

4-step distilled LoRA for MiniMax-H3 text-to-video+audio (T2VA). Trained on Ascend NPU with data-free distillation; merge into the base model and inject base_schedule before vllm-omni / MindIE-SD deployment.

Files

| File | Description |

|------|-------------|

| minimax_h3_4step_lora_flashgen_v1.0_768p_bf16.safetensors | Student LoRA, rank 64, bf16 |

| merge_lora_ckpt.py | Merge LoRA into base model and inject base_schedule |

Training config

| Item | Value |

|------|-------|

| Method | Distribution matching distillation (VSD, no GAN), trained on Ascend NPU |

| Task | T2VA |

| Inference steps | 4 |

| Resolution | 1344×768, 5.2s |

| base_schedule | [1.0, 0.7, 0.4, 0.15, 0.0] |

| LoRA targets | qkv_proj, out_proj, fc1, fc2, adaln_proj.linear |

| LoRA rank | 64 |

Usage

Requires base model MiniMaxAI/MiniMax-H3.

Merge with merge_lora_ckpt.py before vllm-omni / MindIE deployment:

python merge_lora_ckpt.py \
  ${MODEL_ROOT}/FL2VA \
  minimax_h3_4step_lora_flashgen_v1.0_768p_bf16.safetensors \
  ./minimax-h3-4step-flashgen

export MODEL=./minimax-h3-4step-flashgen/FL2VA

Deployment (MindIE-SD / vllm-omni)

For Ascend NPU inference and serving, see the MindIE-SD deployment guide:

• MiniMax-H3 推理部署文档（含 4 步蒸馏权重合并与启动）
• MindIE-SD 仓库：Ascend/MindIE-SD