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:
- c958d774b0f37f825249a604fc75d40152d7de2ea1ecf9c4bdd2be6bffaf5762
- Size of remote file:
- 492 MB
- SHA256:
- 88373e0edd336099e13b68709420e62f1dd7fce3cb08027208d436b3f7ddce48
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