AndrewAtanov/simclr-pytorch
PyTorch implementation of SimCLR: supports multi-GPU training and closely reproduces results
This project helps machine learning researchers and engineers efficiently train advanced image recognition models without requiring a large dataset of labeled images. By taking unlabeled image datasets, it produces powerful image encoders that can then be used to build classifiers with significantly less labeled data. It is ideal for those working on computer vision tasks who need to extract meaningful features from images.
211 stars. No commits in the last 6 months.
Use this if you are developing computer vision models and want to leverage self-supervised learning to improve performance or reduce the need for extensive manual image labeling.
Not ideal if you are a business user looking for a no-code solution or if your primary goal is not related to advanced image representation learning.
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211
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42
Language
Jupyter Notebook
License
MIT
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Last pushed
Apr 29, 2024
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