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", 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
epoch 5 - step 0
Browse files- checkpoint.tar +1 -1
- diffusion_pytorch_model.safetensors +1 -1
- samples/sample_37500.png +0 -0
- samples/sample_39100.png +0 -0
- samples/sample_39200.png +0 -0
- samples/sample_39300.png +0 -0
checkpoint.tar
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