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
Download unet/diffusion_pytorch_model.bin from AlejandroLanaspa/faceless: direct link, hf CLI and curl.
- Browser
- Download file 3.46 GB
-
https://huggingface.co/AlejandroLanaspa/faceless/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://AlejandroLanaspa/faceless/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/AlejandroLanaspa/faceless/resolve/main/unet/diffusion_pytorch_model.bin
3.46 GB
- Xet hash:
- c32db703311213e7271fc74644e1472d86dabd6f9404807186cb87137343201d
- Size of remote file:
- 3.46 GB
- SHA256:
- f04b18ecb78ee4441c609ac6ba163631d19ff499e1ab82e46ca53f9a15d082e5
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