Instructions to use mfrayha/me with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mfrayha/me with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mfrayha/me", 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:
- 60c2be7e0ebf866ad8174c6d8eb47520142adacc7d31f582e751ca9c810a1ff1
- Size of remote file:
- 492 MB
- SHA256:
- 131490d5690e8fe50c02885c762dc7dfcced7a7cbcf8554789514a2d3ef51f5f
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