Instructions to use ishitangupta/test_model_10_vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ishitangupta/test_model_10_vae with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ishitangupta/test_model_10_vae", 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:
- 3bea6bd2f301674685db1e4a13a283a7bb72e80d690399d5d586f8166b0b9fd5
- Size of remote file:
- 169 MB
- SHA256:
- d75bf779a2aabd3fc0c3b8f198b698370dd3729c0a45ed6765e6528baaa46f15
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