Showing 1689 open source projects for "compiler python linux"

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  • 1
    Axolotl

    Axolotl

    Go ahead and axolotl questions

    Axolotl is a powerful and flexible framework for fine-tuning large language models on custom datasets. Built for researchers and developers, Axolotl simplifies the process of adapting LLMs for specific tasks, including chat, code generation, and instruction following. It supports a wide variety of model architectures and offers out-of-the-box optimization strategies for efficient training.
    Downloads: 4 This Week
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  • 2
    robosuite

    robosuite

    A Modular Simulation Framework and Benchmark for Robot Learning

    Robosuite is a modular and extensible simulation framework for robotic manipulation tasks, built on top of MuJoCo. Developed by the ARISE Initiative, Robosuite offers a set of standardized benchmarks and customizable environments designed to advance research in robotic manipulation, control, and imitation learning. It emphasizes realistic simulations and ease of use for both single-task and multi-task learning.
    Downloads: 4 This Week
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  • 3
    TextWorld

    TextWorld

    ​TextWorld is a sandbox learning environment for the training

    TextWorld is a learning environment designed to train reinforcement learning agents to play text-based games, where actions and observations are entirely in natural language. Developed by Microsoft Research, TextWorld focuses on language understanding, planning, and interaction in complex, narrative-driven environments. It generates games procedurally, enabling scalable testing of agents’ natural language processing and decision-making abilities.
    Downloads: 4 This Week
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  • 4
    Letta

    Letta

    Letta (formerly MemGPT) is a framework for creating LLM services

    Letta is an AI-powered task automation framework designed to handle workflow automation, natural language commands, and AI-driven decision-making.
    Downloads: 4 This Week
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  • 5
    AudioLM - Pytorch

    AudioLM - Pytorch

    Implementation of AudioLM audio generation model in Pytorch

    Implementation of AudioLM, a Language Modeling Approach to Audio Generation out of Google Research, in Pytorch It also extends the work for conditioning with classifier free guidance with T5. This allows for one to do text-to-audio or TTS, not offered in the paper. Yes, this means VALL-E can be trained from this repository. It is essentially the same. This repository now also contains a MIT licensed version of SoundStream. It is also compatible with EnCodec, however, be aware that it...
    Downloads: 4 This Week
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  • 6
    Megatron

    Megatron

    Ongoing research training transformer models at scale

    Megatron is a large, powerful transformer developed by the Applied Deep Learning Research team at NVIDIA. This repository is for ongoing research on training large transformer language models at scale. We developed efficient, model-parallel (tensor, sequence, and pipeline), and multi-node pre-training of transformer based models such as GPT, BERT, and T5 using mixed precision. Megatron is also used in NeMo Megatron, a framework to help enterprises overcome the challenges of building and...
    Downloads: 4 This Week
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  • 7
    DI-engine

    DI-engine

    OpenDILab Decision AI Engine

    DI-engine is a unified reinforcement learning (RL) platform for reproducible and scalable RL research. It offers modular pipelines for various RL algorithms, with an emphasis on production-level training and evaluation.
    Downloads: 3 This Week
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  • 8
    Wikipedia2Vec

    Wikipedia2Vec

    A tool for learning vector representations of words and entities

    Wikipedia2Vec is an embedding learning tool that creates word and entity vector representations from Wikipedia, enabling NLP models to leverage structured and contextual knowledge.
    Downloads: 3 This Week
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  • 9
    DOLMA

    DOLMA

    Data and tools for generating and inspecting OLMo pre-training data

    DOLMA (Data Optimization and Learning for Model Alignment) is a framework designed to manage large-scale datasets for training and fine-tuning language models efficiently.
    Downloads: 3 This Week
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  • 10
    Obsei

    Obsei

    Obsei is a low code AI powered automation tool

    Obsei is an automated no-code/low-code AI-powered text observation and analysis framework, designed for extracting insights from unstructured text data such as social media, reviews, and logs.
    Downloads: 3 This Week
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  • 11
    SciSpaCy

    SciSpaCy

    A full spaCy pipeline and models for scientific/biomedical documents

    ScispaCy is a spaCy extension optimized for processing biomedical and scientific text, providing domain-specific NLP models for tasks like named entity recognition (NER) and dependency parsing.
    Downloads: 3 This Week
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  • 12
    AutoGPTQ

    AutoGPTQ

    An easy-to-use LLMs quantization package with user-friendly apis

    AutoGPTQ is an implementation of GPTQ (Quantized GPT) that optimizes large language models (LLMs) for faster inference by reducing their computational footprint while maintaining accuracy.
    Downloads: 3 This Week
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  • 13
    STORM

    STORM

    An LLM-powered knowledge curation system that researches topics

    STORM is an open-source virtual assistant framework developed by Stanford's OVAL lab. It is designed for creating natural language interfaces and assistants that can interact with APIs, databases, and services in a modular way.
    Downloads: 3 This Week
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  • 14
    Quadratic

    Quadratic

    Data science spreadsheet with Python & SQL

    Quadratic enables your team to work together on data analysis to deliver better results, faster. You already know how to use a spreadsheet, but you’ve never had this much power before. Quadratic is a Web-based spreadsheet application that runs in the browser and as a native app (via Electron). Our goal is to build a spreadsheet that enables you to pull your data from its source (SaaS, Database, CSV, API, etc) and then work with that data using the most popular data science tools today...
    Downloads: 5 This Week
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  • 15
    OpenVINO Training Extensions

    OpenVINO Training Extensions

    Trainable models and NN optimization tools

    OpenVINO™ Training Extensions provide a convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference. When ote_cli is installed in the virtual environment, you can use the ote command line interface to perform various actions for templates related to the chosen task type, such as running, training, evaluating, exporting, etc. ote train trains a model (a particular model template) on a dataset and saves results in two files. ote...
    Downloads: 5 This Week
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  • 16
    AIHawk

    AIHawk

    AIHawk aims to easy job hunt process by automating job applications

    AIHawk is an AGPL‑licensed AI agent focused on automating job applications. It scrapes job listings from corporate sites (or LinkedIn in forks) and uses LLMs to generate tailored applications, streamlining the process across multiple platforms—dubbed “revolutionary” by mainstream tech outlets.
    Downloads: 1 This Week
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  • 17
    spaCy models

    spaCy models

    Models for the spaCy Natural Language Processing (NLP) library

    spaCy is designed to help you do real work, to build real products, or gather real insights. The library respects your time, and tries to avoid wasting it. It's easy to install, and its API is simple and productive. spaCy excels at large-scale information extraction tasks. It's written from the ground up in carefully memory-managed Cython. If your application needs to process entire web dumps, spaCy is the library you want to be using. Since its release in 2015, spaCy has become an industry...
    Downloads: 12 This Week
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  • 18
    NErlNet

    NErlNet

    Nerlnet is a framework for research and development

    NErlNet is a research-grade framework for distributed machine learning over IoT and edge devices. Built with Erlang (Cowboy HTTP), OpenNN, and Python (Flask), it enables simulation of clusters on a single machine or real deployment across heterogeneous devices.
    Downloads: 0 This Week
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  • 19
    Atomic Agents

    Atomic Agents

    Building AI agents, atomically

    The Atomic Agents framework is designed around the concept of atomicity to be an extremely lightweight and modular framework for building Agentic AI pipelines and applications without sacrificing developer experience and maintainability. The framework provides a set of tools and agents that can be combined to create powerful applications. It is built on top of Instructor and leverages the power of Pydantic for data and schema validation and serialization. All logic and control flows are...
    Downloads: 2 This Week
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  • 20
    smolagents

    smolagents

    Agents write python code to call tools and orchestrate other agents

    This library is the simplest framework out there to build powerful agents. We provide our definition in this page, where you’ll also find tips for when to use them or not (spoilers: you’ll often be better off without agents). smolagents is a lightweight framework for building AI agents using large language models (LLMs). It simplifies the development of AI-driven applications by providing tools to create, train, and deploy language model-based agents.
    Downloads: 2 This Week
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  • 21
    TorchMetrics

    TorchMetrics

    Machine learning metrics for distributed, scalable PyTorch application

    TorchMetrics is a collection of 80+ PyTorch metrics implementations and an easy-to-use API to create custom metrics. Your data will always be placed on the same device as your metrics. You can log Metric objects directly in Lightning to reduce even more boilerplate. The module-based metrics contain internal metric states (similar to the parameters of the PyTorch module) that automate accumulation and synchronization across devices! Automatic accumulation over multiple batches. Automatic...
    Downloads: 2 This Week
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  • 22
    PySyft

    PySyft

    Data science on data without acquiring a copy

    Most software libraries let you compute over the information you own and see inside of machines you control. However, this means that you cannot compute on information without first obtaining (at least partial) ownership of that information. It also means that you cannot compute using machines without first obtaining control over those machines. This is very limiting to human collaboration and systematically drives the centralization of data, because you cannot work with a bunch of data...
    Downloads: 6 This Week
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  • 23
    Animated Drawings

    Animated Drawings

    Code to accompany "A Method for Animating Children's Drawings"

    AnimatedDrawings is a framework that converts user sketches or line drawings into fully animated 2D motion sequences using learned motion priors. The idea is that you draw a simple static figure (stick figure, silhouette, or contour lines), and the system produces plausible skeletal motion (walking, jumping, dancing) that adheres to the drawn shape constraints. The architecture separates shape embedding (to understand user-drawn geometry) from motion embedding / generation (to produce...
    Downloads: 15 This Week
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  • 24
    BEIR

    BEIR

    A Heterogeneous Benchmark for Information Retrieval

    BEIR is a benchmark framework for evaluating information retrieval models across various datasets and tasks, including document ranking and question answering.
    Downloads: 2 This Week
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  • 25
    Chonkie

    Chonkie

    The no-nonsense RAG chunking library

    Chonkie is an AI-powered framework designed for building conversational agents and chatbots with natural language understanding and multi-turn conversation support.
    Downloads: 2 This Week
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