Instructions to use JGuo666/TurboClear with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JGuo666/TurboClear 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("JGuo666/TurboClear", 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
Upload fusion/fusion_module.pth with huggingface_hub
Browse files- fusion/fusion_module.pth +3 -0
fusion/fusion_module.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:2c313a7ebbb156a02d971034e90bb3749b2a670e5e736210da60c73ba0cc1d13
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size 59468
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