Instructions to use TensorStack/AutoEncoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TensorStack/AutoEncoder with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TensorStack/AutoEncoder", 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
- Xet hash:
- 2f5097632c5c1b0e18f8410847b870ce8babe1c48de7f9c0502c0cd2a6ff46f8
- Size of remote file:
- 624 MB
- SHA256:
- 2f46bc743439b6ffce657b5805ec5d8214204c0aaf6cf6426a8b66b8cc8356b3
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