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:
- b82ec3db54b3edb616f5d5b2f7338aa93525d6a87126f18f48f11fd4f8a923cd
- Size of remote file:
- 6.71 GB
- SHA256:
- 7581d7e0663fd27a3c7b2b242a7af5eda89e57c67e3259017f8b77d83b930479
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