Text-to-Image
Diffusers
Safetensors
English
pixel-art
diffusion
ddpm
ddim
unet
classifier-free-guidance
32x32
trained-from-scratch
Instructions to use viknesh100/PtahX32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use viknesh100/PtahX32 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("viknesh100/PtahX32", 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 data/cache.pt from viknesh100/PtahX32: direct link, hf CLI and curl.
- Browser
- Download file 160 MB
-
https://huggingface.co/viknesh100/PtahX32/resolve/main/data/cache.pt
- Command line
-
hf download hf://viknesh100/PtahX32/data/cache.pt
-
curl -L -o cache.pt https://huggingface.co/viknesh100/PtahX32/resolve/main/data/cache.pt
160 MB
- Xet hash:
- 11d3b89b7a8400c8730e366fd3e7120f2d9ecab20cb593ff0e818f0d2ba6eb16
- Size of remote file:
- 160 MB
- SHA256:
- 52ee6d82caa9fc282cdc4eba6a3cc720e04614bb708a864ce8777d351d0ea3a6
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