Instructions to use Genrator/1st with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Genrator/1st with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Genrator/1st", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 1d6bae9815278b5a6997613f664f81dbd3de2963249403d63208ae3647c347c5
- Size of remote file:
- 4.27 GB
- SHA256:
- 90c4969b47fdf31c01444faec7273dc502d1e1ce33a93d0eafce427e26df3bd8
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