Instructions to use camenduru/memo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use camenduru/memo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("camenduru/memo", 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:
- ebab0efec3052bb65cd861f3f9790ae4b16bd796c6105d2bbd7254f4a66fa681
- Size of remote file:
- 3.43 GB
- SHA256:
- 064447cf3e66fe1cc5812aa4b5e88716ebb46f27fdf6dff146f0e82469da5537
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