Showing 4 open source projects for "word processor python"

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    Surya

    Surya

    Implementation of the Surya Foundation Model for Heliophysics

    Surya is an open‑source, AI‑based foundation model for heliophysics developed collaboratively by NASA (via the IMPACT AI team) and IBM. Named after the Sanskrit word for “sun,” Surya is trained on nine years of high‑resolution solar imagery from NASA’s Solar Dynamics Observatory (SDO). It is designed to forecast solar phenomena—such as flares, solar wind, irradiance, and active region behavior—by predicting future solar images with a sophisticated long–short vision transformer architecture,...
    Downloads: 3 This Week
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    RoBERTa for Chinese

    RoBERTa for Chinese

    RoBERTa Chinese pre-training model: RoBERTa for Chinese

    RoBERTa for Chinese is a Chinese RoBERTa pretrained model repository for language understanding tasks. 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...
    Downloads: 0 This Week
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  • 3
    MUSE

    MUSE

    A library for Multilingual Unsupervised or Supervised word Embeddings

    MUSE is a framework for learning multilingual word embeddings that live in a shared space, enabling bilingual lexicon induction, cross-lingual retrieval, and zero-shot transfer. It supports both supervised alignment with seed dictionaries and unsupervised alignment that starts without parallel data by using adversarial initialization followed by Procrustes refinement. The code can align pre-trained monolingual embeddings (such as fastText) across dozens of languages and provides standardized...
    Downloads: 0 This Week
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  • 4
    mms-300m-1130-forced-aligner

    mms-300m-1130-forced-aligner

    CTC-based forced aligner for audio-text in 158 languages

    mms-300m-1130-forced-aligner is a multilingual forced alignment model based on Meta’s MMS-300M wav2vec2 checkpoint, adapted for Hugging Face’s Transformers library. It supports forced alignment between audio and corresponding text across 158 languages, offering broad multilingual coverage. The model enables accurate word- or phoneme-level timestamping using Connectionist Temporal Classification (CTC) emissions. Unlike other tools, it provides significant memory efficiency compared to the TorchAudio forced alignment API. Users can integrate it easily through the Python package ctc-forced-aligner, and it supports GPU acceleration via PyTorch. The alignment pipeline includes audio processing, emission generation, tokenization, and span detection, making it suitable for speech analysis, transcription syncing, and dataset creation. ...
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