Instructions to use xkronosx/AutoEncoder-mnist-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xkronosx/AutoEncoder-mnist-32 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xkronosx/AutoEncoder-mnist-32", torch_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: 202 Bytes
276b561 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"_class_name": "ResNetEncoderDecoder",
"_diffusers_version": "0.27.2",
"base_filters": 32,
"in_channels": 1,
"latent_channels": 1,
"latent_size": [
16,
16
],
"num_blocks": 2
}
|