Instructions to use ProgramerSalar/fineTune_dit_checkpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ProgramerSalar/fineTune_dit_checkpoint with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ProgramerSalar/fineTune_dit_checkpoint", 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
- Xet hash:
- d59e68142a25ef662f88cee8d834dece4370d303b24d4406ba7147e996a7e8df
- Size of remote file:
- 7.89 GB
- SHA256:
- 90699132955b267df82e68d95b3d9c937b917b387fba7cfa145cf7230bb87a16
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.