Instructions to use Poomz/loreitup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Poomz/loreitup with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Poomz/loreitup", 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
Download vae/diffusion_pytorch_model.safetensors from Poomz/loreitup: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/Poomz/loreitup/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://Poomz/loreitup/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/Poomz/loreitup/resolve/main/vae/diffusion_pytorch_model.safetensors
335 MB
- Xet hash:
- 8f8c779b59bd181792b501c295c0753807dc6275e6c56847d28ad39bdcecca59
- Size of remote file:
- 335 MB
- SHA256:
- 703abdcd7c389316b5128faa9b750a530ea1680b453170b27afebac5e4db30c4
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