Instructions to use AML-group10/5e-4_10_hyperparameter_tuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AML-group10/5e-4_10_hyperparameter_tuning with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("segmind/tiny-sd", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("AML-group10/5e-4_10_hyperparameter_tuning") 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:
- 21be5f44ecf37d1a67e5c56ca33bd4760d147eb6911949829dda9788a2287a6b
- Size of remote file:
- 889 kB
- SHA256:
- d67ca3d21e91486163f31d8ea3ef089e8fef174576e4364731a458d45df7c668
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