Instructions to use dataautogpt3/CALAMITY with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dataautogpt3/CALAMITY with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dataautogpt3/CALAMITY", dtype=torch.bfloat16, device_map="cuda") prompt = "7-Vectors, glitched skyline, high rise ruins, retrowave, occult, glitching, retrofuturistic, glitch art, artifacts, circuitry demon, glitched screen, synthetic, english, scanlines, chromatic aberration, bad quality, red-pink, crt, vhs, noise, grain, highly detailed, 4k, synthetic anime" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- cff231aeb7c094c7b2deb25adb7475267c2cd5732ba24f012c68b275ffd5055c
- Size of remote file:
- 5.14 GB
- SHA256:
- f7b534c2a06cb6d0a093838c79561237a09d728211280b69feb366e697aee8ee
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.