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
Delete unet/requirements.txt
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unet/requirements.txt
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transformers==4.36.2
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torch==2.0.1
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torchvision==0.15.2
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torchaudio==2.0.2
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numpy==1.24.4
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scipy==1.10.1
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scikit-image==0.21.0
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opencv-python==4.7.0.72
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pillow==9.4.0
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diffusers==0.25.0
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transformers==4.36.2
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accelerate==0.26.1
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matplotlib==3.7.4
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tqdm==4.64.1
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config==0.5.1
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einops==0.7.0
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onnxruntime==1.16.2
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basicsr
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av
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fvcore
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cloudpickle
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omegaconf
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pycocotools
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