Showing 3 open source projects for "data masking"

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    OpenAI Privacy Filter

    OpenAI Privacy Filter

    Bidirectional token-classification model for identifiable info

    OpenAI Privacy Filter is an open-weight machine learning model designed to detect and mask personally identifiable information in text with high efficiency and contextual awareness. It operates as a bidirectional token classification system that labels sensitive data in a single forward pass rather than generating text sequentially, enabling fast processing for large datasets. The model supports long-context inputs, allowing it to analyze extensive documents without chunking, which improves...
    Downloads: 2 This Week
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  • 2
    RoBERTa for Chinese

    RoBERTa for Chinese

    RoBERTa Chinese pre-training model: RoBERTa for Chinese

    ...It provides TensorFlow and PyTorch-compatible model releases trained on large-scale Chinese text. The project follows the main RoBERTa training ideas, including removing next sentence prediction, using more diverse data, training longer, increasing batch size, and tuning optimization settings. Its training data includes news, community discussion, encyclopedia content, and other broad Chinese text sources. The repository also describes whole word masking for Chinese and provides examples for loading and fine-tuning models on sentence-pair matching tasks. ...
    Downloads: 0 This Week
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  • 3
    MAE (Masked Autoencoders)

    MAE (Masked Autoencoders)

    PyTorch implementation of MAE

    MAE (Masked Autoencoders) is a self-supervised learning framework for visual representation learning using masked image modeling. It trains a Vision Transformer (ViT) by randomly masking a high percentage of image patches (typically 75%) and reconstructing the missing content from the remaining visible patches. This forces the model to learn semantic structure and global context without supervision. The encoder processes only the visible patches, while a lightweight decoder reconstructs the...
    Downloads: 0 This Week
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