Instructions to use fev12345/Image_Generation_model_HA_Author with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fev12345/Image_Generation_model_HA_Author with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fev12345/Image_Generation_model_HA_Author", 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:
- fe9ed3e0bcbae57bef7761b045df800adbbfe5af105065acd68fcd4fc6688188
- Size of remote file:
- 5.95 GB
- SHA256:
- 45bee064703ab9be38fb816c2f9fddadb08c2a30920f686a6fc15b8d09c2cc83
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