Showing 8 open source projects for "documentation"

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  • 1
    DocsGPT

    DocsGPT

    GPT-powered chat for documentation search & assistance

    DocsGPT is a cutting-edge open-source solution that streamlines the process of finding information in project documentation. With its integration of powerful GPT models, developers can easily ask questions about a project and receive accurate answers. Say goodbye to time-consuming manual searches, and let DocsGPT help you quickly find the information you need. Try it out and see how it revolutionizes your project documentation experience. Contribute to its development and be a part of the future of AI-powered assistance.
    Downloads: 0 This Week
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  • 2
    Diffusers

    Diffusers

    State-of-the-art diffusion models for image and audio generation

    ...We recommend installing Diffusers in a virtual environment from PyPi or Conda. For more details about installing PyTorch and Flax, please refer to their official documentation.
    Downloads: 0 This Week
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  • 3
    Edge GPT

    Edge GPT

    Reverse engineered API of Microsoft's Bing Chat

    ...The repository gained popularity because it provided a practical way to experiment with Bing Chat programmatically, including CLI-style usage patterns and developer-oriented documentation. As with many reverse-engineered clients, it depended on upstream behavior that could change, and the project’s lifecycle reflected that reality. The repository was later archived, meaning it is read-only and no longer actively maintained, but it remains a reference point for how developers approached unofficial access to Bing Chat. ...
    Downloads: 1 This Week
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  • 4
    Point-E

    Point-E

    Point cloud diffusion for 3D model synthesis

    ...The repository includes inference scripts, utilities for converting point clouds to meshes (e.g. via signed distance function regression), sample notebooks, and weight checkpoints. It also provides documentation on limitations, usage instructions, and example outputs.
    Downloads: 0 This Week
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  • 5
    Texar-PyTorch

    Texar-PyTorch

    Integrating the Best of TF into PyTorch, for Machine Learning

    Texar-PyTorch is a toolkit aiming to support a broad set of machine learning, especially natural language processing and text generation tasks. Texar provides a library of easy-to-use ML modules and functionalities for composing whatever models and algorithms. The tool is designed for both researchers and practitioners for fast prototyping and experimentation. Texar-PyTorch was originally developed and is actively contributed by Petuum and CMU in collaboration with other institutes. A mirror...
    Downloads: 0 This Week
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  • 6
    GANformer

    GANformer

    Generative Adversarial Transformers

    This is an implementation of the GANformer model, a novel and efficient type of transformer, explored for the task of image generation. The network employs a bipartite structure that enables long-range interactions across the image, while maintaining computation of linearly efficiency, that can readily scale to high-resolution synthesis. The model iteratively propagates information from a set of latent variables to the evolving visual features and vice versa, to support the refinement of...
    Downloads: 0 This Week
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  • 7
    TorchGAN

    TorchGAN

    Research Framework for easy and efficient training of GANs

    The torchgan package consists of various generative adversarial networks and utilities that have been found useful in training them. This package provides an easy-to-use API which can be used to train popular GANs as well as develop newer variants. The core idea behind this project is to facilitate easy and rapid generative adversarial model research. TorchGAN is a Pytorch-based framework for designing and developing Generative Adversarial Networks. This framework has been designed to...
    Downloads: 0 This Week
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  • 8
    commit-autosuggestions

    commit-autosuggestions

    A tool that AI automatically recommends commit messages

    ...CodeBERT: A Pre-Trained Model for Programming and Natural Languages introduces a pre-trained model in a combination of Program Language and Natural Language(PL-NL). It also introduces the problem of converting code into natural language (Code Documentation Generation). We can use CodeBERT to create a model that generates a commit message when code is added. However, most code changes are not made only by add of the code, and some parts of the code are deleted. We plan to slowly conquer languages that are not currently supported. To run this project, you need a flask-based inference server (GPU) and a client (commit module). ...
    Downloads: 1 This Week
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