awesome-repositories.com
博客
MCP
awesome-repositories.com

通过 AI 驱动的搜索,发现最优秀的开源仓库。

探索精选搜索开源替代品自托管软件博客网站地图
项目MCP 服务器关于排名机制媒体报道
法律隐私政策服务条款
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·

37 个仓库

Awesome GitHub RepositoriesFormat Conversion Utilities

Tools for translating between native database types and standard array formats.

Distinct from Vector Data Formats: Distinct from Vector Data Formats: focuses on the conversion process rather than the format definition.

Explore 37 awesome GitHub repositories matching data & databases · Format Conversion Utilities. Refine with filters or upvote what's useful.

Awesome Format Conversion Utilities GitHub Repositories

用 AI 发现最棒的仓库。我们将通过 AI 为您搜索最匹配的仓库。
  • pgvector/pgvectorpgvector 的头像

    pgvector/pgvector

    21,787在 GitHub 上查看↗

    Vector similarity search extension for PostgreSQL.

    Translates data between native database types and standard array formats for simplified importing and exporting.

    Cpostgresvector-searchembeddings
    在 GitHub 上查看↗21,787
  • janeczku/calibre-webjaneczku 的头像

    janeczku/calibre-web

    17,500在 GitHub 上查看↗

    Calibre-web is a self-hosted web application that provides a browser-based interface for browsing, managing, and reading digital book collections stored in a library database. It functions as a comprehensive library management system, allowing users to organize large collections, edit metadata, and perform automated content updates through a centralized administrative dashboard. The platform distinguishes itself by integrating directly with external infrastructure to extend the capabilities of a standard digital library. It supports remote storage mapping to host files on cloud providers, uti

    Utilizes external binary tools to perform on-the-fly e-book format conversions for improved device compatibility.

    Fluentcalibreebookebook-manager
    在 GitHub 上查看↗17,500
  • apprenticeharper/dedrm_toolsapprenticeharper 的头像

    apprenticeharper/DeDRM_tools

    15,104在 GitHub 上查看↗

    DeDRM_tools is a software suite designed to automate the removal of digital rights management from personal e-book files. By stripping restrictive encryption layers during the import process, the utility enables users to manage their digital libraries and convert protected files into open formats for use across various reading devices. The system operates through a modular architecture that utilizes plugin-based event interception to hook into host applications. It performs cryptographic key extraction by scanning local configuration files and memory, applying algorithm-specific decryption to

    Removes digital rights management from e-book files to enable format conversion and cross-device reading.

    Python
    在 GitHub 上查看↗15,104
  • mikefarah/yqmikefarah 的头像

    mikefarah/yq

    14,913在 GitHub 上查看↗

    This tool is a command-line processor designed for querying, updating, and transforming structured data files. It functions as a versatile engine for manipulating YAML, JSON, TOML, and XML documents, allowing users to perform complex operations directly from the terminal. By utilizing a path-based expression language, it enables precise navigation and modification of data structures within configuration files and infrastructure-as-code workflows. What distinguishes this tool is its ability to perform in-place document mutations while preserving original formatting, comments, and metadata. It

    The tool transforms structured data into property file format, supporting custom separators, array bracket notation, and automatic string encapsulation.

    Gobashclicsv
    在 GitHub 上查看↗14,913
  • janishar/mit-deep-learning-book-pdfjanishar 的头像

    janishar/mit-deep-learning-book-pdf

    14,142在 GitHub 上查看↗

    This project is a digital collection of academic material on deep learning provided as a machine learning educational resource. It delivers the complete textbook and individual chapters in portable document format for offline study and research. The repository includes electronic publication versions of the textbooks optimized for digital reading devices and e-book readers. It functions as a segmented document repository, providing the text both as a full volume and split into individual chapters to allow for targeted reading.

    Provides converted electronic publication versions of the textbook for compatibility with e-book readers.

    Javabookchapterclear
    在 GitHub 上查看↗14,142
  • thu-mig/yolov10THU-MIG 的头像

    THU-MIG/yolov10

    11,316在 GitHub 上查看↗

    YOLOv10 is a PyTorch computer vision library and real-time vision framework designed for locating and identifying multiple objects in images and video streams. It functions as an end-to-end object detector that optimizes for high-speed deployment and detection precision. The project is distinguished by an NMS-free detection architecture that predicts a single bounding box per object, eliminating the need for non-maximum suppression post-processing to reduce inference latency. It further optimizes for edge hardware through scalable weights and a quantization-friendly structure that facilitates

    Provides utilities for converting model weights into optimized formats compatible with various hardware accelerators.

    Python
    在 GitHub 上查看↗11,316
  • blinkdl/chatrwkvBlinkDL 的头像

    BlinkDL/ChatRWKV

    9,492在 GitHub 上查看↗

    ChatRWKV is an open-source frontend and GPU-accelerated inference engine designed for interacting with RWKV recurrent neural network language models. It provides a self-hosted web chat interface and a specialized client for generating human-like text using a linear-complexity architecture. The project utilizes a GPU-accelerated backend that employs custom CUDA kernels and dynamic model format conversion to increase processing speed and reduce memory overhead. It manages conversation history through state-based context management, updating a fixed-size hidden state to maintain a constant memor

    Transforms model weights into specialized formats to accelerate loading and optimize GPU memory allocation.

    Pythonchatbotchatgptlanguage-model
    在 GitHub 上查看↗9,492
  • dusty-nv/jetson-inferencedusty-nv 的头像

    dusty-nv/jetson-inference

    8,734在 GitHub 上查看↗

    jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU hardware. Its primary purpose is to enable real-time computer vision and AI inference at the edge with low latency and high throughput. The project distinguishes itself through high-performance streaming analytics and the ability to execute concurrent AI pipelines on auto-grade silicon. It provides specialized support for multi-sensor stream processing, utilizing zero-copy data transport to load camera frames directly into GPU memory. The codebase covers a broad surface of capabiliti

    Translates model weights between different formats to ensure interoperability between training frameworks and inference engines.

    C++caffecomputer-visiondeep-learning
    在 GitHub 上查看↗8,734
  • tiiny-ai/powerinferTiiny-AI 的头像

    Tiiny-AI/PowerInfer

    8,714在 GitHub 上查看↗

    PowerInfer is a high-performance local large language model inference engine and sparse inference framework. It provides a runtime for executing models on consumer-grade hardware, utilizing a GPU acceleration backend to optimize tensor operations for graphics processors. The system distinguishes itself through a sparse inference framework that increases generation speed by skipping computations based on activation sparsity in model weights. It includes a GGUF model converter for transforming weights and metadata into a unified binary format, as well as an OpenAI API compatible server for inte

    Transforms model weights into specialized formats required for optimized sparse inference.

    C++large-language-modelsllamallm
    在 GitHub 上查看↗8,714
  • xpixelgroup/basicsrXPixelGroup 的头像

    XPixelGroup/BasicSR

    8,297在 GitHub 上查看↗

    BasicSR is a PyTorch-based image restoration toolbox and framework designed for training and deploying deep learning models to upscale, denoise, and deblur images and videos. It serves as a comprehensive system for image super-resolution and video quality restoration, providing the necessary infrastructure to recover fine visual details and increase pixel density. The project distinguishes itself through specialized toolkits for facial image enhancement and high-fidelity face synthesis, as well as a dedicated video quality restoration suite that utilizes deformable convolutions and generative

    Translates neural network weights and architectures between different versions to ensure compatibility.

    Pythonbasicsrbasicvsrdfdnet
    在 GitHub 上查看↗8,297
  • ml-explore/mlx-examplesml-explore 的头像

    ml-explore/mlx-examples

    8,254在 GitHub 上查看↗

    This repository provides a collection of reference implementations and code examples for training and deploying machine learning models using the MLX framework. It serves as a practical guide for executing distributed training, fine-tuning large language models, converting model weights, and implementing multimodal generative workflows. The project distinguishes itself through specialized examples for local hardware execution, featuring weight quantization to reduce memory usage and low-rank adaptation for parameter-efficient fine-tuning. It also includes scripts for transforming external mod

    Ships scripts for transforming model weights and formats into MLX-compatible versions with precision quantization.

    Pythonmlx
    在 GitHub 上查看↗8,254
  • carson-katri/dream-texturescarson-katri 的头像

    carson-katri/dream-textures

    8,168在 GitHub 上查看↗

    Dream Textures is a Stable Diffusion integration for Blender that provides tools for text-to-image generation, depth projection, and node-based processing within a 3D environment. It functions as an AI texture generator capable of producing image textures and concept art from text prompts and scene renders. The system features a depth-to-image projection tool that maps generated imagery onto 3D models using depth data for spatial alignment. It also includes a node-based AI image processor for creating procedural visual effects and a dedicated toolset for AI-assisted inpainting and outpainting

    Transforms external model weights into a compatible internal format for use within the environment.

    Pythonaiblenderblender-addon
    在 GitHub 上查看↗8,168
  • tingsongyu/pytorch_tutorialTingsongYu 的头像

    TingsongYu/PyTorch_Tutorial

    8,018在 GitHub 上查看↗

    This project is a comprehensive collection of educational examples and reference implementations for building vision and language models using PyTorch. It serves as a deep learning tutorial covering the end-to-end process of developing neural networks, from initial architecture definition to final production deployment. The repository provides detailed guides on implementing a wide range of domain-specific models, including convolutional neural networks for object detection and segmentation, as well as transformer and recurrent architectures for natural language processing. It emphasizes gene

    Transforms PyTorch weights into binary formats compatible with high-performance engines like TensorRT.

    Python
    在 GitHub 上查看↗8,018
  • santinic/audiblezsantinic 的头像

    santinic/audiblez

    7,811在 GitHub 上查看↗

    Audiblez is a text-to-speech audiobook generator that converts digital e-books into spoken audio files. The system processes written documents using speech synthesis and configurable voice profiles to produce audiobooks. The tool utilizes a graphical interface to manage the conversion workflow and task orchestration. It employs CUDA-accelerated processing to offload neural network computations to the GPU, increasing the speed of audio generation. The system includes capabilities for chapter-based file parsing and selective chapter conversion. Users can adjust synthesis parameters, including

    Offers a visual interface for transforming digital book chapters into audio files.

    Pythonaudiobooksepubkokoro
    在 GitHub 上查看↗7,811
  • wang-xinyu/tensorrtxwang-xinyu 的头像

    wang-xinyu/tensorrtx

    7,802在 GitHub 上查看↗

    tensorrtx is a computer vision inference engine and model implementation library designed for graphics processor acceleration. It provides a framework for optimizing deep learning models through a GPU inference optimizer, a deep learning model converter for transforming weights from frameworks like TensorFlow and PyTorch, and a custom plugin library to implement operations not natively supported by the TensorRT API. The project distinguishes itself through a comprehensive collection of pre-defined network implementations, ranging from various YOLO versions and DETR transformers for object det

    Converts PyTorch pretrained weights into specialized execution formats for GPU optimization.

    C++arcfacecrnndetr
    在 GitHub 上查看↗7,802
  • kohya-ss/sd-scriptskohya-ss 的头像

    kohya-ss/sd-scripts

    7,133在 GitHub 上查看↗

    sd-scripts is a suite of utilities designed for fine-tuning generative models, preprocessing datasets, and converting model weights. It provides a collection of scripts for executing Stable Diffusion training through methods such as DreamBooth, textual inversion, and full fine-tuning, alongside a framework for creating and managing Low-Rank Adaptation weights. The project features specialized capabilities for model weight conversion between different architectures and precision formats. It includes tools for merging adaptation weights into base models, extracting weights from trained models,

    Transforms model weights between different architectures and precision formats for compatibility.

    Python
    在 GitHub 上查看↗7,133
  • qqwweee/keras-yolo3qqwweee 的头像

    qqwweee/keras-yolo3

    7,116在 GitHub 上查看↗

    This project is an object detection framework implementing the YOLOv3 architecture using Keras and TensorFlow. It functions as a deep learning vision model and computer vision toolset designed to locate and classify multiple entities within images and video streams using bounding boxes. The system includes a multi-GPU inference engine to distribute computational loads across several graphics processing units. It also provides a pipeline for creating custom object detectors by retraining pre-trained weights on annotated datasets to recognize user-defined object classes. The framework covers m

    Provides utilities to convert model weights between different deep learning frameworks to ensure environment compatibility.

    Python
    在 GitHub 上查看↗7,116
  • facebookresearch/metaseqfacebookresearch 的头像

    facebookresearch/metaseq

    6,546在 GitHub 上查看↗

    Metaseq 是一个 Transformer 序列建模工具包,专为使用开放预训练权重进行序列到序列模型的训练、微调和部署而设计。它为大语言模型训练提供了一个全面的框架,包括用于序列数据集处理的专用工具,以及用于通过 API 请求生成文本的独立推理服务器。 该项目具有用于模型量化的专用实用程序,可将参数精度降低到 8 位,从而降低内存使用量并提高推理速度。它还包括一个检查点转换流水线,将模型权重转换为针对高性能推理引擎优化的结构。 该框架通过使用张量并行和分片数据并行,支持跨 GPU 集群的大规模训练。其他功能涵盖 NLP 数据集准备、用于迁移学习的预训练权重加载,以及用于进度可视化的训练指标跟踪。

    Provides tools to transform model weights from standard formats into specialized versions for high-performance inference.

    Python
    在 GitHub 上查看↗6,546
  • rmcrackan/libationrmcrackan 的头像

    rmcrackan/Libation

    5,703在 GitHub 上查看↗

    Libation is a comprehensive audiobook management system designed to download, decrypt, and organize Audible audiobooks. It integrates account authentication, library synchronization, DRM removal, and format transcoding into a single desktop application with a plugin-free graphical interface and a built-in theme editor. The project distinguishes itself through a batch library synchronization engine that scans all configured Audible accounts in one pass, a metadata tag rewriting system that corrects chapter markers and cover art after decryption, and a template-based file naming engine that con

    Downloads audiobooks in multiple audio formats based on user configuration.

    C#
    在 GitHub 上查看↗5,703
  • leejet/stable-diffusion.cppleejet 的头像

    leejet/stable-diffusion.cpp

    5,430在 GitHub 上查看↗

    stable-diffusion.cpp is a high-performance C++ inference engine designed for generating images and video from text prompts using Stable Diffusion models. It functions as a latent diffusion model runtime and a lightweight machine learning framework that enables local diffusion model execution on consumer hardware. The project distinguishes itself as a CPU-based image generator capable of running without a dedicated GPU. It employs a specialized C++ tensor backend and cross-backend hardware abstraction to dispatch compute tasks across different processor instruction sets and graphics APIs. The

    Transforms complex model tensors into streamlined binary layouts optimized for sequential memory access.

    C++aicplusplusdiffusion
    在 GitHub 上查看↗5,430
上一个12下一个
  1. Home
  2. Data & Databases
  3. Vector Data Formats
  4. Format Conversion Utilities

探索子标签

  • Audiobook Format Converters1 个子标签Utilities that transform digital book files into spoken audio formats. **Distinct from E-book Format Converters:** Distinct from E-book Format Converters which change text-to-text formats; this transforms text-to-audio.
  • E-book Format Converters3 个子标签Utilities that transform digital book files between formats for device compatibility. **Distinct from Format Conversion Utilities:** Distinct from Format Conversion Utilities: focuses specifically on e-book format transformations using external binary tools.
  • Model Weight Conversions2 个子标签Transformations of neural network weights into specialized execution formats for hardware optimization. **Distinct from Format Conversion Utilities:** Distinct from Format Conversion Utilities: specifically targets model weights for GPU execution rather than general vector data types.
  • Property File ExportersTools for serializing structured data into property file formats with support for custom delimiters and notation. **Distinct from Format Conversion Utilities:** Distinct from Format Conversion Utilities: focuses specifically on the property file serialization target rather than general format translation.