Showing 4 open source projects for "text word prediction"

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  • 1
    gitsigns.nvim

    gitsigns.nvim

    Git integration for buffers

    Super fast git decorations implemented purely in lua/teal. Signs for added, removed, and changed lines. Asynchronous using luv. Navigation between hunks. Stage hunks (with undo). Preview diffs of hunks (with word diff). Customizable (signs, highlights, mappings, etc). Status bar integration. Git blame a specific line using virtual text. Hunk text object. Automatically follow files moved in the index. Live intra-line word diff. Ability to display deleted/changed lines via virtual lines. Support for yadm. Support for detached working trees. ...
    Downloads: 1 This Week
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  • 2
    torch-rnn

    torch-rnn

    Efficient, reusable RNNs and LSTMs for torch

    The torch-rnn project is a lightweight and efficient implementation of recurrent neural networks built on the Torch framework, focusing on flexibility and reusability for sequence modeling tasks. It provides implementations of standard RNNs and long short-term memory networks, enabling users to train models for tasks such as text generation, language modeling, and sequence prediction. The repository emphasizes simplicity and performance, offering a streamlined pipeline for preprocessing data, training models, and sampling outputs. It includes tools for handling datasets, converting text into structured formats, and managing checkpoints during training. By leveraging Torch’s modular design, the project allows users to experiment with different architectures and hyperparameters with minimal overhead. ...
    Downloads: 0 This Week
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  • 3
    char-rnn

    char-rnn

    Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN)

    char-rnn is a classic codebase for training multi-layer recurrent neural networks on raw text to build character-level language models that learn to predict the next character in a sequence. It supports common recurrent architectures including vanilla RNNs as well as LSTM and GRU variants, letting users compare behavior and output quality across model types. It is straightforward: you provide a single text file, train the model to minimize next-character prediction loss, then sample from the trained network to generate new text one character at a time in the style of the dataset. ...
    Downloads: 0 This Week
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  • 4
    WordGrinder is a light-weight character-cell word processor designed for text entry on the console, supporting Unicode and styled text. It provides a clean, easy-to-use interface that gets out of your way and get the job done. We've moved! Go visit http://cowlark.com/wordgrinder.
    Downloads: 0 This Week
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