Showing 163 open source projects for "lightweight linux"

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  • 1
    Punica

    Punica

    Serving multiple LoRA finetuned LLM as one

    Punica is a system designed to efficiently serve multiple LoRA-fine-tuned large language models within a shared GPU environment. LoRA is a parameter-efficient fine-tuning method that allows developers to adapt large pretrained models to specific tasks by adding lightweight adapter layers rather than retraining the entire model. Punica introduces a serving architecture that allows multiple LoRA adapters to share the same base model during inference, significantly reducing memory consumption...
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  • 2
    ConsistencyDecoder

    ConsistencyDecoder

    Consistency Distilled Diff VAE

    ConsistencyDecoder is a Python package from OpenAI that introduces an improved decoding method for variational autoencoders (VAEs) used in Stable Diffusion pipelines. Instead of relying solely on the standard GAN or VAE decoder, this approach leverages a Consistency Distilled Diff VAE, designed to produce higher-quality and more stable outputs from encoded latents. The project provides a simple API for encoding with a Stable Diffusion VAE and decoding using the new consistency model,...
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  • 3
    Neural Network Intelligence

    Neural Network Intelligence

    AutoML toolkit for automate machine learning lifecycle

    Neural Network Intelligence is an open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate feature engineering, neural architecture search, hyperparameter tuning and model compression. The tool manages automated machine learning (AutoML) experiments, dispatches and runs experiments'...
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  • 4
    Lightning-Hydra-Template

    Lightning-Hydra-Template

    PyTorch Lightning + Hydra. A very user-friendly template

    Convenient all-in-one technology stack for deep learning prototyping - allows you to rapidly iterate over new models, datasets and tasks on different hardware accelerators like CPUs, multi-GPUs or TPUs. A collection of best practices for efficient workflow and reproducibility. Thoroughly commented - you can use this repo as a reference and educational resource. Not fitted for data engineering - the template configuration setup is not designed for building data processing pipelines that...
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  • 5
    FastViT

    FastViT

    This repository contains the official implementation of research

    FastViT is an efficient vision backbone family that blends convolutional inductive biases with transformer capacity to deliver strong accuracy at mobile and real-time inference budgets. Its design pursues a favorable latency-accuracy Pareto curve, targeting edge devices and server scenarios where throughput and tail latency matter. The models use lightweight attention and carefully engineered blocks to minimize token mixing costs while preserving representation power. Training and inference...
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  • 6
    Language Models

    Language Models

    Explore large language models in 512MB of RAM

    languagemodels is a lightweight Python library designed to simplify experimentation with large language models while maintaining extremely low hardware requirements. The project focuses on enabling developers and students to explore language model capabilities without needing expensive GPUs or large cloud infrastructures. By using small and optimized models, the library allows LLM inference to run in environments with limited resources, sometimes requiring only a few hundred megabytes of...
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  • 7
    simpleaichat

    simpleaichat

    Python package for easily interfacing with chat apps

    simpleaichat is a Python library that streamlines building conversational apps with large language models by offering a minimal, developer-friendly interface. It aims to abstract the boilerplate of prompt management, message history, and streaming while leaving core Python control in your hands. The package emphasizes simplicity over heavy frameworks, making it ideal for scripts, notebooks, and small services that need LLMs without architectural lock-in. It supports structured responses and...
    Downloads: 1 This Week
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  • 8
    Free-Auto-GPT

    Free-Auto-GPT

    Free AutoGPT enables autonomous AI tasks without paid APIs

    Free Auto GPT is an open source project that delivers a simplified version of an autonomous AI agent capable of completing tasks independently. It allows users to run an AutoGPT-style system without relying on paid OpenAI APIs, making it more accessible for experimentation and personal use. Free Auto GPT can take a goal, break it into smaller steps, and execute actions in a loop to achieve results with minimal human input. Designed for ease of use, the project focuses on removing cost...
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  • 9
    picoGPT

    picoGPT

    An unnecessarily tiny implementation of GPT-2 in NumPy

    picoGPT is a minimal implementation of the GPT-2 language model designed to demonstrate how transformer-based language models work at a conceptual level. The repository focuses on educational clarity rather than production performance, implementing the core components of the GPT architecture in a concise and readable way. It allows users to understand how tokenization, transformer layers, attention mechanisms, and autoregressive text generation operate in modern large language models. The...
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  • 10
    minimalRL-pytorch

    minimalRL-pytorch

    Implementations of basic RL algorithms with minimal lines of codes

    minimalRL is a lightweight reinforcement learning repository that implements several classic algorithms using minimal PyTorch code. The project is designed primarily as an educational resource that demonstrates how reinforcement learning algorithms work internally without the complexity of large frameworks. Each algorithm implementation is contained within a single file and typically ranges from about 100 to 150 lines of code, making it easy for learners to inspect the entire implementation...
    Downloads: 0 This Week
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  • 11
    AnnLite

    AnnLite

    A fast embedded library for approximate nearest neighbor search

    AnnLite is a lightweight and embeddable library for fast and filterable approximate nearest neighbor search (ANNS). It allows to search for nearest neighbors in a dataset of millions of points with a Pythonic API. A simple API is designed to be used with Python. It is easy to use and intuitive to set up to production. The library uses a highly optimized approximate nearest neighbor search algorithm (HNSW) to search for nearest neighbors. The library allows you to search for nearest neighbors...
    Downloads: 0 This Week
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  • 12
    Bot on Anything

    Bot on Anything

    Large model-based chatbot builder that can quickly integrate AI models

    Bot on Anything is a versatile open-source AI chatbot builder that lets developers connect large language models such as ChatGPT, Claude, and Gemini to virtually any messaging platform, website, or interface with minimal configuration. At its heart, the project abstracts away the glue logic between AI model APIs and disparate application “channels,” enabling the same bot logic to run in Slack, Telegram, Gmail, enterprise tools, web UIs, or command-line terminals. Configuration is handled...
    Downloads: 2 This Week
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  • 13
    Multi-Agent Particle Envs

    Multi-Agent Particle Envs

    Code for a multi-agent particle environment used in a paper

    Multiagent Particle Environments is a lightweight framework for simulating multi-agent reinforcement learning tasks in a continuous observation space with discrete action settings. It was originally developed by OpenAI and used in the influential paper Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. The environment provides simple particle-based worlds with simulated physics, where agents can move, communicate, and interact with each other. Scenarios are designed to...
    Downloads: 0 This Week
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  • 14
    TextBox

    TextBox

    A text generation library with pre-trained language models github.com

    TextBox 2.0 is an up-to-date text generation library based on Python and PyTorch focusing on building a unified and standardized pipeline for applying pre-trained language models to text generation. From a task perspective, we consider 13 common text generation tasks such as translation, story generation, and style transfer, and their corresponding 83 widely-used datasets. From a model perspective, we incorporate 47 pre-trained language models/modules covering the categories of general,...
    Downloads: 0 This Week
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  • 15
    ostRAT

    ostRAT

    OpenSourceTelegramRAT - Remote PC access via Telegram Bot.

    ostRAT is free and open source. GPLv3 Сomputer remote control software. Works via telegram bot. A lot of functions, for example: - Screenshot: sends a screenshot - Off: turns off the computer - Url: opens entered link - Write: sends your text to the computer - Move: changes mouse location with x and y - and more! WARNING: Using the bot is recommended only on your device. Failure to comply with the recommendation may result in criminal liability.
    Downloads: 0 This Week
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  • 16
    nlpaug

    nlpaug

    Data augmentation for NLP

    This Python library helps you with augmenting nlp for your machine learning projects. Visit this introduction to understand Data Augmentation in NLP. Augmenter is the basic element of augmentation while Flow is a pipeline to orchestra multi augmenters together.
    Downloads: 0 This Week
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  • 17
    ASRT Speech Recognition

    ASRT Speech Recognition

    A Deep-Learning-Based Chinese Speech Recognition System

    ASRT is an end-to-end deep-learning Chinese ASR system built with TensorFlow/Keras, using convolution + CTC and a Max-Entropy HMM language model. It provides a REST/gRPC server backend and client SDKs in multiple languages (Python, Java, Go, Windows). Notably lightweight, it performs well without needing GPU acceleration and runs across platforms, targeting developers and researchers building Chinese voice interfaces.
    Downloads: 0 This Week
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  • 18
    Apache MXNet (incubating)

    Apache MXNet (incubating)

    A flexible and efficient library for deep learning

    Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable.
    Downloads: 0 This Week
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  • 19
    MAE (Masked Autoencoders)

    MAE (Masked Autoencoders)

    PyTorch implementation of MAE

    MAE (Masked Autoencoders) is a self-supervised learning framework for visual representation learning using masked image modeling. It trains a Vision Transformer (ViT) by randomly masking a high percentage of image patches (typically 75%) and reconstructing the missing content from the remaining visible patches. This forces the model to learn semantic structure and global context without supervision. The encoder processes only the visible patches, while a lightweight decoder reconstructs the...
    Downloads: 0 This Week
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  • 20
    Tez

    Tez

    Tez is a super-simple and lightweight Trainer for PyTorch

    Tez is a super-simple and lightweight Trainer for PyTorch. It also comes with many utils that you can use to tackle over 90% of deep learning projects in PyTorch. tez (तेज़ / تیز) means sharp, fast & active. This is a simple, to-the-point, library to make your PyTorch training easy. This library is in early-stage currently! So, there might be breaking changes. Currently, tez supports cpu, single gpu and multi-gpu & tpu training. More coming soon! Using tez is super-easy. We don't want you to...
    Downloads: 0 This Week
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  • 21
    DrQA

    DrQA

    Reading Wikipedia to Answer Open-Domain Questions

    DrQA is an open-domain question answering system that reads large text corpora—famously Wikipedia—to answer natural language questions with extractive spans. It follows a two-stage pipeline: a fast document retriever first narrows down candidate articles, and a neural machine reader then predicts the exact answer span from those passages. The retriever relies on classic IR features (like TF-IDF and n-gram statistics) to remain lightweight and scalable to millions of documents. The reader is...
    Downloads: 0 This Week
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  • 22
    FixRes

    FixRes

    Reproduces results of "Fixing the train-test resolution discrepancy"

    FixRes is a lightweight yet powerful training methodology for convolutional neural networks (CNNs) that addresses the common train-test resolution discrepancy problem in image classification. Developed by Facebook Research, FixRes improves model generalization by adjusting training and evaluation procedures to better align input resolutions used during different phases. The approach is simple but highly effective, requiring no architectural modifications and working across diverse CNN...
    Downloads: 0 This Week
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  • 23
    fastNLP

    fastNLP

    fastNLP: A Modularized and Extensible NLP Framework

    fastNLP is a lightweight framework for natural language processing (NLP), the goal is to quickly implement NLP tasks and build complex models. A unified Tabular data container simplifies the data preprocessing process. Built-in Loader and Pipe for multiple datasets, eliminating the need for preprocessing code. Various convenient NLP tools, such as Embedding loading (including ELMo and BERT), intermediate data cache, etc.. Provide a variety of neural network components and recurrence models...
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  • 24
    EfficientNet Keras

    EfficientNet Keras

    Implementation of EfficientNet model. Keras and TensorFlow Keras

    This repository contains a Keras (and TensorFlow Keras) reimplementation of EfficientNet, a lightweight convolutional neural network architecture achieving state-of-the-art accuracy with an order of magnitude fewer parameters and FLOPS, on both ImageNet and five other commonly used transfer learning datasets. Convolutional Neural Networks (ConvNets) are commonly developed at a fixed resource budget, and then scaled up for better accuracy if more resources are available. In this paper, we...
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  • 25
    VideoPose3D

    VideoPose3D

    Efficient 3D human pose estimation in video using 2D keypoint

    VideoPose3D is a deep learning framework that reconstructs 3D human poses from 2D keypoint sequences extracted from videos. It builds on top of convolutional and temporal networks that map 2D joint coordinates over time to consistent 3D skeletons, enabling robust motion capture without specialized sensors. The model is trained on large motion capture datasets and can generalize well to unseen environments by leveraging temporal context for smoothing and error correction. By using only 2D...
    Downloads: 1 This Week
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