Instructions to use deepcs233/VividFace with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use deepcs233/VividFace with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("deepcs233/VividFace", 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
- Xet hash:
- 8aa067f963b7d4d82d20b4275d54dbd3ff99ae038e6a861eb465343f4586e899
- Size of remote file:
- 1.72 GB
- SHA256:
- f51658e17640f730a59d693ab330935574914b08d6cc9692836572521e80cc85
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.