Instructions to use aboudcode/unet-generation-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use aboudcode/unet-generation-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("aboudcode/unet-generation-model", 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:
- 8499c6bc5e4925fea2027a73be3956fa15ebc1334be32a3c5a27cebe33cc8629
- Size of remote file:
- 3.44 GB
- SHA256:
- d27cd69d4a0aa32105087a619f32a51bc087e133be93fe23da92f3c0bcc07d79
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