Instructions to use Reshad/reshad-face-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Reshad/reshad-face-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Reshad/reshad-face-model", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- df33c3b7cd828fdd7cec6a262405eb98b85c709c5d985d5c7325673ffe2365df
- Size of remote file:
- 492 MB
- SHA256:
- 951be8d0223fb14dc6d0d572e045aabd1a512c02b045defc08d0c3c5c4c4da7d
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