Feature Extraction
Diffusers
Safetensors
English
autoencoder
vision-foundation-model
dinov2
dinov3
mae
siglip2
pae
Instructions to use BiliSakura/PAE-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/PAE-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("BiliSakura/PAE-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
File size: 1,308 Bytes
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"_class_name": "PAEDecoder",
"decoder_patch_size": 16,
"encoder_config_path": "facebook/vit-mae-large",
"encoder_hidden_size": 1024,
"encoder_input_size": 256,
"encoder_num_heads": 16,
"encoder_patch_size": 16,
"latent_dim": 32,
"latent_mean": [
0.6328125,
1.1171875,
-1.140625,
0.95703125,
0.80859375,
-0.8046875,
0.43359375,
-0.263671875,
1.28125,
0.341796875,
-0.291015625,
-0.80859375,
0.71484375,
-0.89453125,
-1.046875,
0.96875,
-1.484375,
0.71875,
0.1767578125,
0.9140625,
0.9453125,
-1.0,
1.0859375,
-1.3515625,
-1.1015625,
-0.625,
0.53125,
0.640625,
-1.3984375,
0.4921875,
1.1015625,
0.515625
],
"latent_multiplier": 1.0,
"latent_std": [
0.5546875,
0.328125,
0.32421875,
0.3203125,
0.458984375,
0.3515625,
0.55078125,
0.470703125,
0.38671875,
0.51171875,
0.490234375,
0.515625,
0.380859375,
0.486328125,
0.3515625,
0.5390625,
0.3046875,
0.6015625,
0.404296875,
0.482421875,
0.3828125,
0.373046875,
0.408203125,
0.447265625,
0.4765625,
0.390625,
0.45703125,
0.45703125,
0.4375,
0.416015625,
0.45703125,
0.484375
]
}
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