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:
- bed6c3c5e43282d2687285cd67d2531d89021e7b7a16c690341685c20d66d849
- Size of remote file:
- 1.45 GB
- SHA256:
- 425f0dfa227dee5d0ff3d9720563370810409a439c302ca74f0f944057ce55c5
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