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:
- 87cc8e0e0d8d716efc69c673fdfe4a484e3cdd088ec6d527cab18948a7367947
- Size of remote file:
- 353 kB
- SHA256:
- 61a9cdd70903d32184b73de5c19807765fbf8c3341d1b4e1a6087b35078c5b38
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