Instructions to use AlejandroLanaspa/faceless with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AlejandroLanaspa/faceless with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AlejandroLanaspa/faceless", 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:
- 6cd8abd3c539ed648ee9cb8e307f49a113a6050aa22cea1b114672e74ea36775
- Size of remote file:
- 2.58 GB
- SHA256:
- d8eb5352ad4c17f038a2a578a9f8f596004d1cc07b52e00affb1b5a359ffe7e7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.