Instructions to use Keshabwi66/SmartLugaModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Keshabwi66/SmartLugaModel with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Keshabwi66/SmartLugaModel", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f62488aa575f96cee122734dee82518435dfac3ba52e376aa42f966dd158462
- Size of remote file:
- 335 MB
- SHA256:
- 98a14dc6fe8d71c83576f135a87c61a16561c9c080abba418d2cc976ee034f88
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