Instructions to use BAAI/Emu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BAAI/Emu with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BAAI/Emu", 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:
- bcb9ea7cf94cf41ecafb8528b6401f2bbca8796307fd921e95f86b67eeac9867
- Size of remote file:
- 28.5 GB
- SHA256:
- ae5d009276d47389aaa16d73e9c81904ef0221fb0d4529b081f4a7a3955688c9
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