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:
- 0764ea408af39dce74d3d8eb61df63badc51782fb258d452559b94fbc79d7de5
- Size of remote file:
- 7.89 GB
- SHA256:
- fa78faba398b24c31c230a63d18d9e5dc88a44dcf55fa010238dff04e5a746f0
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