Instructions to use clem/maxdekdt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use clem/maxdekdt with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("clem/maxdekdt", 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:
- 0f525b0b3438834a34430993f06da1377667b45baac58150a49fb9f7f478656e
- Size of remote file:
- 1.36 GB
- SHA256:
- 442e2e2692272b51c5ba633681051aa2e273fe7c156dd905bcf3d37d6df7cf04
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