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:
- 340d57c316a93d32e58156d1a3127bfb20d2a1ec65db5c9a5f39928bded3a97d
- Size of remote file:
- 1.36 GB
- SHA256:
- c3e254d7b61353497ea0be2c4013df4ea8f739ee88cffa0ba58cd085459ed565
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