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
Delete pixeldit/__init__.py with huggingface_hub
Browse files- pixeldit/__init__.py +0 -17
pixeldit/__init__.py
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from .pipeline import PixelDiTPipeline
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from .modeling_pixeldit import load_pixeldit
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from .modeling_pixeldit_hf import PixelDiTModel
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from .configuration_pixeldit import PixelDiTConfig
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from .text_encoder_gemma import GemmaEncoder
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from .text_encoder_qwen import QwenEncoder
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from .scheduling_flow import FlowScheduler
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__all__ = [
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"PixelDiTPipeline",
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"load_pixeldit",
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"PixelDiTModel",
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"PixelDiTConfig",
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"GemmaEncoder",
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"QwenEncoder",
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"FlowScheduler",
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]
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