{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "yzmblog-dmad--generate-dmad-clips-in-comfyui",
 "repo": "Yzmblog/DMAD",
 "repo_url": "https://github.com/Yzmblog/DMAD",
 "repo_slug": "yzmblog-dmad",
 "title": "Render DMAD clips in ComfyUI with ready-made workflows",
 "page_title": "How to render DMAD clips in ComfyUI with ready-made workflows with DMAD",
 "summary": "Load the ComfyUI-layout DMAD LoRA and a ready-to-run workflow to make 4-step or 8-step clips with audio.",
 "who": "A ComfyUI user with a 16 to 24 GB GPU who wants a visual node graph instead of the command line.",
 "problem": "Command-line inference is hard for artists who already build their video pipelines in ComfyUI.",
 "outcome": "A 15 s video with audio rendered from a ComfyUI workflow, using the ready-to-run 4-step or 8-step graph.",
 "steps": [
  "Download the ComfyUI key layout file with `hf download ZhengmingYu/DMAD --include \"minimax_h3/*_comfyui.safetensors\" --local-dir ckpt` (inferred from the README file names). (inferred, check the README)",
  "Open the ready-to-run workflow described in comfyui/README.md for the 24 GB GPU setup.",
  "Load the file `dmad_minimax_h3_4step_lora_critic_comfyui.safetensors` in the LoRA loader.",
  "Set the sampler to `lcm` and the scheduler to `simple`, then run the graph."
 ],
 "agent_prompt": "In the Yzmblog/DMAD repo, open the ComfyUI workflow described in comfyui/README.md and load dmad_minimax_h3_4step_lora_critic_comfyui.safetensors with the lcm sampler and simple scheduler. Expected output: a 15 s video with audio for the prompt <your prompt>. Verify that the sampler and scheduler names match the README before running.",
 "agents": [
  "any"
 ],
 "difficulty": "Intermediate",
 "time": "2 hours",
 "basis": "readme",
 "caveat": "The ready-to-run workflows are documented for 16 to 24 GB GPUs, so an 8 GB GPU needs the separate 5 s workflow that the README links.",
 "category": "Content",
 "tags": [
  "Content"
 ],
 "lang": "python",
 "requirements": [
  "A CUDA GPU: 80 GB for the default path, 8 GB and up with --low-vram",
  "Python 3.12 with conda and PyTorch for CUDA 12.6",
  "About 170 GB of free disk space for the MiniMax-H3 base components",
  "A Hugging Face account that has accepted the MiniMax H3 Community License"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.8,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/yzmblog-dmad/generate-dmad-clips-in-comfyui/",
 "md": "https://dedupedai.com/use-cases/yzmblog-dmad/generate-dmad-clips-in-comfyui/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/yzmblog-dmad--generate-dmad-clips-in-comfyui.json",
 "api_version": "v1"
}