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", 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
File size: 303 Bytes
491af34 fa8167b 491af34 2e87f45 491af34 | 1 2 3 4 5 6 7 8 9 | {
"_class_name": "PixelDiTPipeline",
"_diffusers_version": "0.31.0",
"transformer": ["diffusers", "PixelDiTModel"],
"scheduler": ["diffusers", "FlowMatchEulerDiscreteScheduler"],
"text_encoder": ["transformers", "PreTrainedModel"],
"tokenizer": ["transformers", "PreTrainedTokenizerFast"]
}
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