Instructions to use Falah/babylon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Falah/babylon with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Falah/babylon", 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 Falah/babylon: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/Falah/babylon/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Falah/babylon/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Falah/babylon/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- d3238625c51927486c902015b6b4425e8a003d59c82be5de87fa2d21dc15f80e
- Size of remote file:
- 3.44 GB
- SHA256:
- e8438b05da58e4be10ccafebe3484bba074e2a0ae9aab653375e0317120d35bc
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