Instructions to use madtune/pixeldit-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use madtune/pixeldit-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nvidia/PixelDiT-1300M-1024px", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("madtune/pixeldit-diffusers") 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
| { | |
| "_class_name": "PixelDiTPipeline", | |
| "_diffusers_version": "0.38.0", | |
| "_name_or_path": "madtune/pixeldit-diffusers", | |
| "scheduler": [ | |
| "diffusers", | |
| "FlowMatchEulerDiscreteScheduler" | |
| ], | |
| "text_encoder": [ | |
| "transformers", | |
| "Gemma2Model" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "TokenizersBackend" | |
| ], | |
| "transformer": [ | |
| "pixeldit", | |
| "PixelDiTModel" | |
| ] | |
| } | |