Instructions to use Master-AI-Lab/Lumi-Transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Master-AI-Lab/Lumi-Transformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Master-AI-Lab/Lumi-Transformer") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Master-AI-Lab/Lumi-Transformer", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload requirements.txt
Browse files- requirements.txt +11 -0
requirements.txt
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python==3.7.16
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torch==1.9.0+cu111
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torchvision==0.10.0+cu111
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cudatoolkit==10.2.89
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cuda==12.1.1
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timm==0.4.12
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opencv-python==4.4.0.46
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termcolor==1.1.0
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yacs==0.1.8
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pyyaml==6.0
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scipy==1.7.3
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