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  • 1
    dLLM

    dLLM

    dLLM: Simple Diffusion Language Modeling

    dLLM is an open-source framework designed to simplify the development, training, and evaluation of diffusion-based large language models. Unlike traditional autoregressive models that generate text sequentially token by token, diffusion language models generate text through an iterative denoising process that refines masked tokens over multiple steps. This approach allows models to reason over the entire sequence simultaneously and potentially produce more coherent outputs with bidirectional context. The project provides an integrated pipeline that standardizes how diffusion language models are trained, evaluated, and deployed, helping researchers reproduce experiments and compare results more easily. ...
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  • 2
    Learning Interpretability Tool

    Learning Interpretability Tool

    Interactively analyze ML models to understand their behavior

    The Learning Interpretability Tool (LIT, formerly known as the Language Interpretability Tool) is a visual, interactive ML model-understanding tool that supports text, image, and tabular data. It can be run as a standalone server, or inside of notebook environments such as Colab, Jupyter, and Google Cloud Vertex AI notebooks.
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  • 3
    nbdime

    nbdime

    Tools for diffing and merging of Jupyter notebooks

    nbdime provides tools for diffing and merging Jupyter notebooks. Jupyter notebooks are useful, rich media documents stored in a plain text JSON format. This format is relatively easy to parse. However, primitive line-based diff and merge tools do not handle well the logical structure of notebook documents. nbdime, on the other hand, provides “content-aware” diffing and merging of Jupyter notebooks. It understands the structure of notebook documents. Therefore, it can make intelligent...
    Downloads: 0 This Week
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