Instructions to use latentcat/connow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use latentcat/connow with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("latentcat/connow", 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:
- 5ce4c7de47b82c7d5bb451bacb3c0c5e72b0c3f269da019ab5ddc3aac07fc7a0
- Size of remote file:
- 3.42 MB
- SHA256:
- 33bf499feb9cebf78194e3fe8df57f6fb222e1ff84c628f1b9f9298c323adf08
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