Instructions to use matgu23/cntblv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use matgu23/cntblv with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("matgu23/cntblv", 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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 8a4d7b1da0e00523fc6e040f4bc240e613239f50f7efe6c0ea97da607bba4bd1
- Size of remote file:
- 335 MB
- SHA256:
- 465f0c5188254b4f2ce5fa69d6eea4a1f9cec4bc18bf914c4936599a91cfdbe0
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