Instructions to use martineux/cute2diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use martineux/cute2diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("martineux/cute2diffusers", 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
- Draw Things
- DiffusionBee
- Xet hash:
- adf093e34af2a2d5c9f079b479361faf96d6c3e2ae97c149bebb6ca4dbe00431
- Size of remote file:
- 246 MB
- SHA256:
- 31cb53a8b7db9fecead17a209bc97caa0fad90057ddc10e67b8e26357a1caa82
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