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Training Frameworks · Awesome GitHub Repositories

9 repos

Awesome GitHub RepositoriesTraining Frameworks

Comprehensive software libraries that provide the infrastructure and APIs necessary to train machine learning models.

Explore 9 awesome GitHub repositories matching artificial intelligence & ml · Training Frameworks. Refine with filters or upvote what's useful.

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Awesome Training Frameworks GitHub Repositories

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  • sindresorhus/awesome

    sindresorhus/awesome

    438,690GitHubView on GitHub↗

    This project is a community-curated knowledge base that organizes vast technical ecosystems into a hierarchical, human-readable directory. It serves as a comprehensive index of libraries, frameworks, and methodologies, designed to facilitate discovery and professional development across the entire spectrum of software

    awesomeawesome-listlists
  • huggingface/transformers

    huggingface/transformers

    156,730GitHubView on GitHub↗

    Transformers is a comprehensive library for machine learning that provides a unified interface for training, fine-tuning, and deploying transformer-based models. It supports a wide range of tasks, including text classification, language modeling, question answering, and sequence-to-sequence translation, while offering

    Pythonaudiodeep-learningdeepseek
  • rasbt/LLMs-from-scratch

    rasbt/LLMs-from-scratch

    85,529GitHubView on GitHub↗

    This repository serves as an educational framework for building large language models from the ground up. It provides a structured curriculum that guides learners through the end-to-end lifecycle of model development, including data processing, architecture design, and optimization. By focusing on low-level implementat

    Jupyter Notebookaiartificial-intelligencechatbot
  • d2l-ai/d2l-zh

    d2l-ai/d2l-zh

    75,708GitHubView on GitHub↗

    This project is an open-source, interactive educational platform designed to teach deep learning through a comprehensive, code-first curriculum. It provides a structured learning path that covers foundational mathematics, modern neural network architectures, and practical optimization techniques, enabling practitioners

    Pythonbookchinesecomputer-vision
  • awesomedata/awesome-public-datasets

    awesomedata/awesome-public-datasets

    72,846GitHubView on GitHub↗

    This project is a community-maintained, open-access directory of high-quality public datasets. It serves as a centralized reference point for researchers, developers, and data scientists to locate reliable information sources across a wide spectrum of industries and scientific fields. By providing a structured index, t

    aaron-swartzawesome-public-datasetsdatasets
  • tesseract-ocr/tesseract

    tesseract-ocr/tesseract

    72,460GitHubView on GitHub↗

    Tesseract is a neural network-based optical character recognition engine designed to convert scanned images and digital documents into machine-readable, searchable text. It functions as both a command-line utility for automating large-scale digitization workflows and a cross-platform library that can be embedded into d

    C++hacktoberfestlstmmachine-learning
  • keras-team/keras

    keras-team/keras

    63,858GitHubView on GitHub↗

    Keras is a high-level deep learning framework designed for constructing and training neural networks through the composition of modular, functional layers. It serves as a comprehensive modeling toolkit that provides standardized procedures for defining, evaluating, and deploying complex architectures. By utilizing a di

    Pythondata-sciencedeep-learningjax
  • CorentinJ/Real-Time-Voice-Cloning

    CorentinJ/Real-Time-Voice-Cloning

    59,355GitHubView on GitHub↗

    This project is a neural text-to-speech engine and voice cloning toolkit designed to generate synthetic speech that mimics the vocal characteristics of a target speaker. It functions as a real-time audio synthesizer, utilizing a deep learning pipeline to convert written text into high-fidelity speech output with minima

    Pythondeep-learningpythonpytorch
  • karpathy/nanoGPT

    karpathy/nanoGPT

    53,461GitHubView on GitHub↗

    nanoGPT is a lightweight engine for training and fine-tuning transformer-based language models from scratch. It provides a minimalist codebase designed for educational exploration and rapid experimentation with neural network architectures, utilizing self-attention and feed-forward layers to process sequences and predi

    Python

Explore sub-tags

  • API FrameworksComprehensive APIs for distributed and accelerated training.
  • Artificial Intelligence FrameworksLibraries and platforms that provide the foundational tools for building, training, and deploying neural networks.
  • Large Language Model Training FrameworksSpecialized tools for training transformer-based models across single or multi-GPU environments.
Model Training Frameworks
Infrastructure and libraries for building and training custom language models from scratch.
  • Model Training PipelinesEnd-to-end workflows and scripts for sourcing datasets, training models, and validating performance across various machine learning tasks.
  • Training and Evaluation PipelinesAutomated workflows for executing model training, epoch iteration, and validation dataset management.