Instructions to use egerdm/jhemali with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use egerdm/jhemali with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("egerdm/jhemali", 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:
- 9f50fc129affabcd102d5621eff8b3b2303a4ab49379014823d8d9043a384289
- Size of remote file:
- 492 MB
- SHA256:
- 6e3a457aaa58ec71101845fcdb4d3723f94966f0537acc30acb420b5537484d8
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