Instructions to use ZhengmingYu/DMAD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ZhengmingYu/DMAD with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MiniMaxAI/MiniMax-H3", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ZhengmingYu/DMAD") prompt = "A man with short gray hair plays a red electric guitar." output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Inference
- Notebooks
- Google Colab
- Kaggle
Add the sdxl DMAD weights
Browse files
sdxl/dmad_sdxl_1step_frozencritic_unet_fp16.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:0f743d8b2422a8c0f242a1b199f2b3289a872850d9e3c4b3c63d86eade6fb356
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size 5135860277
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sdxl/dmad_sdxl_1step_unet_fp16.bin
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oid sha256:17a765a5033162ed109e4b81c0b637fab744ce5f53dd75c291ccaf785d635d13
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size 5135837515
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sdxl/dmad_sdxl_4step_unet_fp16.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:02c18fd274bf50eec47b5769ee2a18e9d6a6b497e3824cb6cadeb4127b490a5c
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size 5135837515
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