Instructions to use cehongw/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cehongw/output with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cehongw/output", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a <new1> cat" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 9f74f0a7fb59e2b2810aee804e0d2481371da02cfdbdc55551841c7aabc3abff
- Size of remote file:
- 76.7 MB
- SHA256:
- de91b66a2be008509fe47bd0d8514787ce225aeb3c4ef6f65adc9cdd6db0d3f7
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