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 config.json with huggingface_hub
Browse files- config.json +0 -24
config.json
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{
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"architectures": [
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"PixelDiTModel"
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],
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"dtype": "float32",
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"hidden_size": 1536,
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"in_channels": 3,
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"model_type": "pixeldit",
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"num_groups": 24,
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"num_text_blocks": 4,
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"patch_depth": 14,
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"patch_size": 16,
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"pixel_attn_hidden_size": 1152,
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"pixel_depth": 2,
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"pixel_hidden_size": 16,
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"pixel_num_groups": 16,
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"repa_encoder_index": -1,
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"text_rope_theta": 10000.0,
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"transformers_version": "5.9.0",
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"txt_embed_dim": 2304,
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"txt_max_length": 300,
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"use_pixel_abs_pos": true,
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"use_text_rope": true
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}
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