Instructions to use AML-group10/5e-4_15_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_15_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_15_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:
- de7fcbc6229e4d294a3f693eb5a94314712c41da4b4735e73d8d47d37015a75d
- Size of remote file:
- 392 kB
- SHA256:
- 96891618bb137d9c0aec0bcdc86718adcbdddfb4e5309f29fd04c0cda3f764b7
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