Instructions to use hdkkty/MMFace-DiT-Models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hdkkty/MMFace-DiT-Models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hdkkty/MMFace-DiT-Models", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Transformers
How to use hdkkty/MMFace-DiT-Models with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hdkkty/MMFace-DiT-Models", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe8e97f7683e2e5d2025595da5c88a68a7cbd33d7001c984237e35c943b1d2d5
- Size of remote file:
- 681 MB
- SHA256:
- 7bb11b1da63986aaaaefb5ef2100d34109c024ac640cacd9ed697150c1c57f01
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