Instructions to use martineux/etherlabo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use martineux/etherlabo 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/etherlabo", 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:
- bd27dbea3a8cce1d0a5c4807eaf663cff1295a94a30f7e56fef99d5da46040b9
- Size of remote file:
- 167 MB
- SHA256:
- 887c50aa18d25061be0e695ddb89d2ff71496421d11f922666e633125ebd2c30
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