Instructions to use Kurudaz/hyper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Kurudaz/hyper with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Kurudaz/hyper", torch_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
- Xet hash:
- 0e1a0877452d56f26ad719a08ed352aab1bda0762c57308ca92d732ff258a005
- Size of remote file:
- 1.39 GB
- SHA256:
- edc4f52c52826d8e194767decc5f3f6d74d128601b204001b5a7ac626293b521
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