Instructions to use EnD-Diffusers/vaporwave-aesthetic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EnD-Diffusers/vaporwave-aesthetic with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("EnD-Diffusers/vaporwave-aesthetic", dtype=torch.bfloat16, device_map="cuda") prompt = "vapodusk1" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 965d0fd99229b0e2a2e686d27039b13d863f6656418a9df48c971d31bb0d9362
- Size of remote file:
- 3.44 GB
- SHA256:
- bf7eca32901d062c0e0587e80719ca7b0b175ea9ac641338797c18e9e68f7ff0
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