Instructions to use chamuditha4/test22 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use chamuditha4/test22 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("chamuditha4/test22", 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
- Draw Things
- DiffusionBee
- Xet hash:
- f9258446175af2c7a4cfb1fb60ee66f02a44df3a2550a09eb8c597f45691e288
- Size of remote file:
- 246 MB
- SHA256:
- f79bec2680258e5782376bce862507670c142330b21f3a0426522157310c3383
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.