Instructions to use martineux/linesmodelmay with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use martineux/linesmodelmay 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/linesmodelmay", 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:
- f4b27884cc64e737f24ba1821c1a5b08c75229aaabbcf61cea207d6d3f118496
- Size of remote file:
- 167 MB
- SHA256:
- f9f3bf86e95df913a45a4a238709c47f24530c07d10e0f923b0dae2f679799ea
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