Instructions to use ATH-MaaS/TeEFusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ATH-MaaS/TeEFusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ATH-MaaS/TeEFusion", 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
Commit History
-
Improve model card: Add pipeline_tag and enhance sample usage (#3)
Verified signature- Improve model card: Add pipeline_tag and enhance sample usage (e7371cad0668f3f2b0a64ef7732d5acc47413a5a) Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>9cc2434
-
Update README.md
Verified signatured4b5ecb -
Update README.md
Verified signatureec6e3f8 -
Upload folder using huggingface_hub
Verified signature630efd8 -
initial commit
Verified signaturef0a55df