Instructions to use AML-group10/5e-4_20_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_20_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_20_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
Download image_3.png from AML-group10/5e-4_20_hyperparameter_tuning: direct link, hf CLI and curl.
- Browser
- Download file 409 kB
-
https://huggingface.co/AML-group10/5e-4_20_hyperparameter_tuning/resolve/main/image_3.png
- Command line
-
hf download hf://AML-group10/5e-4_20_hyperparameter_tuning/image_3.png
-
curl -L -o image_3.png https://huggingface.co/AML-group10/5e-4_20_hyperparameter_tuning/resolve/main/image_3.png
409 kB

- Xet hash:
- 048175537a51d1c758fd2997a275f2dfe52c195ecf5da43b08302fac64365e84
- Size of remote file:
- 409 kB
- SHA256:
- 7efefac320b7db0928c8cc3cd29c243ad89efd8b873c02136f4c18952b476ca0
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