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:
- 81ae5646cf3ecdb1e4b0ce027f408abde35812a214cceeb7c659a3b33bd1b3a1
- Size of remote file:
- 2.44 GB
- SHA256:
- 107cc359e3c4bce18c53d98686f4b3fe10c4207b6665d89b38b0741270514bfb
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