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  • 1
    imodelsX

    imodelsX

    Interpretable prompting and models for NLP

    ...Fit a better linear model using an LLM to extract embeddings. Fit better decision trees using an LLM to expand features. Finetune a single linear layer on top of LLM embeddings. Use these just a like a sci-kit-learn model. During training, they fit better features via LLMs, but at test-time, they are extremely fast and completely transparent.
    Downloads: 0 This Week
    Last Update:
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  • 2
    solo-learn

    solo-learn

    Library of self-supervised methods for visual representation

    ...We aim at providing SOTA self-supervised methods in a comparable environment while, at the same time, implementing training tricks. The library is self-contained, but it is possible to use the models outside of solo-learn.
    Downloads: 4 This Week
    Last Update:
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  • 3
    Neuro-comma

    Neuro-comma

    Punctuation restoration production-ready model for Russian language

    ...There is several PRs in image repositories, but no response from maintainers. So we decided to change code which we use in production to work with the 3.8 version of Python. In some functions we have 3.9 code, but we still use them, these functions are needed only for development purposes.
    Downloads: 0 This Week
    Last Update:
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