Instructions to use Lotior/mcld with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Lotior/mcld 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("Lotior/mcld", 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:
- bccc05eafacd26bca6323d093cd312012b4710a9cdc06a26312489105b5f54e2
- Size of remote file:
- 3.44 GB
- SHA256:
- e40bb121b7428ecddfd000ee86e6e866962b889e7dd79e6ac51e67dbc9fc5693
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