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: 467 Bytes
068ca33 4ad93f0 068ca33 4ad93f0 068ca33 4ad93f0 068ca33 4ad93f0 068ca33 4ad93f0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"_class_name": "PixelDiTModel",
"_diffusers_version": "0.31.0",
"in_channels": 3,
"num_groups": 24,
"hidden_size": 1536,
"pixel_hidden_size": 16,
"pixel_attn_hidden_size": 1152,
"pixel_num_groups": 16,
"patch_depth": 14,
"pixel_depth": 2,
"num_text_blocks": 4,
"patch_size": 16,
"txt_embed_dim": 2304,
"txt_max_length": 300,
"use_text_rope": true,
"text_rope_theta": 10000.0,
"repa_encoder_index": -1,
"use_pixel_abs_pos": true
} |