Search Results for "compiler python linux" - Page 13
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Showing 1637 open source projects for "compiler python linux"
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RL Games
RL implementations
rl_games is a high-performance reinforcement learning framework optimized for GPU-based training, particularly in environments like robotics and continuous control tasks. It supports advanced algorithms and is built with PyTorch. -
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LightRAG
"LightRAG: Simple and Fast Retrieval-Augmented Generation"
LightRAG is a lightweight Retrieval-Augmented Generation (RAG) framework designed for efficient document retrieval and response generation. It is optimized for speed and lower resource consumption, making it ideal for real-time applications. -
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README-AI
README file generator, powered by AI
README-AI is an automated documentation generator that creates structured README files for GitHub repositories using AI-powered analysis. -
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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. -
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Data-Juicer
Data processing for and with foundation models
Data-Juicer is an open-source data processing and augmentation framework designed to enhance the quality and diversity of datasets for machine learning tasks. It includes a modular pipeline for scalable data transformation. -
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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. -
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Guidance
A guidance language for controlling large language models
Guidance is an efficient programming paradigm for steering language models. With Guidance, you can control how output is structured and get high-quality output for your use case—while reducing latency and cost vs. conventional prompting or fine-tuning. It allows users to constrain generation (e.g. with regex and CFGs) as well as to interleave control (conditionals, loops, tool use) and generation seamlessly. -
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CodiumAI Cover-Agent
CodiumAI Cover-Agent: An AI-Powered Tool for Automated Test Generation
CodiumAI Cover Agent aims to help efficiently increasing code coverage, by automatically generating qualified tests to enhance existing test suites. -
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Quark Agent
Quark Agent - Your AI-powered Android APK Analyst
With Quark Agent, you can perform analyses using only natural language. It creates Quark Script code following your ideas and adjusts the code promptly as you provide feedback. -
Gen AI apps are built with MongoDB AtlasMongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
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EconML
Python Package for ML-Based Heterogeneous Treatment Effects Estimation
EconML is a Python package for estimating heterogeneous treatment effects from observational data via machine learning. This package was designed and built as part of the ALICE project at Microsoft Research with the goal of combining state-of-the-art machine learning techniques with econometrics to bring automation to complex causal inference problems. One of the biggest promises of machine learning is to automate decision-making in a multitude of domains. At the core of many data-driven... -
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BackgroundMattingV2
Real-Time High-Resolution Background Matting
Official repository for the paper Real-Time High-Resolution Background Matting. Our model requires capturing an additional background image and produces state-of-the-art matting results at 4K 30fps and HD 60fps on an Nvidia RTX 2080 TI GPU. -
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PyCaret
An open-source, low-code machine learning library in Python
PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows. It is an end-to-end machine learning and model management tool that speeds up the experiment cycle exponentially and makes you more productive. In comparison with the other open-source machine learning libraries, PyCaret is an alternate low-code library that can be used to replace hundreds of lines of code with few lines only. This makes experiments exponentially fast and efficient... -
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Autolabel
Label, clean and enrich text datasets with LLMs
Autolabel is a Python library to label, clean and enrich datasets with Large Language Models (LLMs). Autolabel data for NLP tasks such as classification, question-answering and named entity recognition, entity matching and more. Seamlessly use commercial and open-source LLMs from providers such as OpenAI, Anthropic, HuggingFace, Google and more. -
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img2dataset
Easily turn large sets of image urls to an image dataset
Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine. Also supports saving captions for url+caption datasets. Opt-out directives: Websites can pass the http headers X-Robots-Tag: noai, X-Robots-Tag: noindex , X-Robots-Tag: noimageai and X-Robots-Tag: noimageindex By default img2dataset will ignore images with such headers. -
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NeMo Curator
Scalable data pre processing and curation toolkit for LLMs
NeMo Curator is a Python library specifically designed for fast and scalable dataset preparation and curation for large language model (LLM) use-cases such as foundation model pretraining, domain-adaptive pretraining (DAPT), supervised fine-tuning (SFT) and paramter-efficient fine-tuning (PEFT). It greatly accelerates data curation by leveraging GPUs with Dask and RAPIDS, resulting in significant time savings. The library provides a customizable and modular interface, simplifying pipeline... -
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SuperDuperDB
Integrate, train and manage any AI models and APIs with your database
Build and manage AI applications easily without needing to move your data to complex pipelines and specialized vector databases. Integrate AI and vector search directly with your database including real-time inference and model training. Just using Python. A single scalable deployment of all your AI models and APIs which is automatically kept up-to-date as new data is processed immediately. No need to introduce an additional database and duplicate your data to use vector search and build on top... -
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Audiomentations
A Python library for audio data augmentation
A Python library for audio data augmentation. Inspired by albumentations. Useful for deep learning. Runs on CPU. Supports mono audio and multichannel audio. Can be integrated in training pipelines in e.g. Tensorflow/Keras or Pytorch. Has helped people get world-class results in Kaggle competitions. Is used by companies making next-generation audio products. Mix in another sound, e.g. a background noise. Useful if your original sound is clean and you want to simulate an environment where... -
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OneFlow
OneFlow is a deep learning framework designed to be user-friendly
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient. An extension for OneFlow to target third-party compiler, such as XLA, TensorRT and OpenVINO etc.CUDA runtime is statically linked into OneFlow. OneFlow will work on a minimum supported driver, and any driver beyond. For more information. Distributed performance (efficiency) is the core technical difficulty of the deep learning framework. OneFlow focuses on performance improvement and heterogeneous... -
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AI Chatbot Framework
Python chatbot framework with Natural Language Understanding
Building a chatbot can sound daunting, but it’s totally doable. AI Chatbot Framework is an AI powered conversational dialog interface built in Python. With this tool, it’s easy to create Natural Language conversational scenarios with no coding efforts whatsoever. The smooth UI makes it effortless to create and train conversations to the bot and it continuously gets smarter as it learns from conversations it has with people. AI Chatbot Framework can live on any channel of your choice... -
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GPT4Free
The official gpt4free repository
gpt4free is an open-source project offering free, unrestricted access to GPT‑4–style language models without requiring an API key. The repository includes scripts and server implementations designed to replicate OpenAI’s GPT‑4 API behavior by leveraging publicly available or self-hosted models. It’s licensed under GPL‑v3. -
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Llama Cookbook
Solve end to end problems using Llama model family
The Llama Cookbook is the official Meta LLaMA guide for inference, fine‑tuning, RAG, and multi-step use-cases. It offers recipes, code samples, and integration examples across provider platforms (WhatsApp, SQL, long context workflows), enabling developers to quickly harness LLaMA models -
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Magentic UI
A research prototype of a human-centered web agent
Magentic-UI is a research prototype developed by Microsoft that serves as a human-centered interface powered by a multi-agent system. It enables users to automate complex web tasks, such as browsing, form filling, and data analysis, while maintaining control over the process. The system emphasizes transparency and user involvement, making it suitable for tasks requiring both automation and human oversight. -
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Notte
Opensource browser using agents
Notte is an open-source browser framework that enables the development and deployment of web-based AI agents. It introduces a perception layer that transforms web pages into structured, navigable maps described in natural language, allowing agents to interact with the internet more effectively. Notte is designed for building scalable and efficient browser-based AI applications. -
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Upsonic
The most reliable AI agent framework that supports MCP
Upsonic is a reliability-focused AI agent framework designed for real-world applications. It enables the development of trusted agent workflows within organizations by incorporating advanced reliability features, such as verification layers and output evaluation systems. The framework supports the Model Context Protocol (MCP), facilitating integration with various tools and enhancing agent capabilities. -
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Binary Ninja MCP
A Binary Ninja plugin, MCP server
The Binary Ninja MCP is a plugin and bridge that integrates Binary Ninja with Large Language Model clients via the Model Context Protocol, enhancing reverse engineering workflows with AI assistance.
