Search Results for "frameworks" - Page 26
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Showing 1053 open source projects for "frameworks"
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AgentGPT
🤖 Assemble, configure & deploy autonomous AI Agents in your browser
🤖 Assemble, configure, and deploy autonomous AI Agents in your browser. 🤖 AgentGPT allows you to configure and deploy Autonomous AI agents. Name your own custom AI and have it embark on any goal imaginable. It will attempt to reach the goal by thinking of tasks to do, executing them, and learning from the results 🚀. By sponsoring this free, open-source project, you not only have the opportunity to have your avatar/logo featured below, but also get the exclusive chance to chat with the... -
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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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FEDML Open Source
The unified and scalable ML library for large-scale training
A Unified and Scalable Machine Learning Library for Running Training and Deployment Anywhere at Any Scale. TensorOpera AI is the next-gen cloud service for LLMs & Generative AI. It helps developers to launch complex model training, deployment, and federated learning anywhere on decentralized GPUs, multi-clouds, edge servers, and smartphones, easily, economically, and securely. Highly integrated with TensorOpera open source library, TensorOpera AI provides holistic support of three... -
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SageMaker Inference Toolkit
Serve machine learning models within a Docker container
...The SageMaker Inference Toolkit implements a model serving stack and can be easily added to any Docker container, making it deployable to SageMaker. This library's serving stack is built on Multi Model Server, and it can serve your own models or those you trained on SageMaker using machine learning frameworks with native SageMaker support. -
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WebArena
Code repo for "WebArena to build Autonomous Agents
WebArena is a realistic web environment designed for building and testing autonomous agents, providing a platform for developing web-based AI agents. -
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State of Open Source AI
Clarity in the current fast-paced mess of Open Source innovation
This repository is the source for a book (or large written work) titled “The State of Open Source AI”. The goal of the project is to bring clarity to the rapidly evolving open-source AI ecosystem by documenting trends, models, tools, standards, deployment practices, and challenges. It acts as both a snapshot and a guide: readers can see what’s “hot now” in open AI infrastructure, what open licensing or governance issues are emerging, how deployment options compare, and what gaps remain.... -
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Chinese Llama 2 7B
The first Chinese LLaMA2 model in the open source community
Chinese Llama 2 7B is an open-source large language model adapted from the LLaMA-2 architecture and optimized for Chinese and bilingual Chinese-English applications. The project provides a version of LLaMA-2 that has been further trained on Chinese data so it can better understand and generate text in Chinese while maintaining compatibility with the original model ecosystem. In addition to the model weights, the repository also includes supervised fine-tuning datasets and training resources... -
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ReplitLM
Inference code and configs for the ReplitLM model family
...The project includes model checkpoints, configuration files, and example code that enable developers to run and experiment with the models locally or within machine learning frameworks. These models are designed specifically for coding workflows and are trained on large datasets of source code covering many programming languages and development environments. The repository also includes documentation and tutorials for integrating the models into development tools, APIs, or research pipelines. Developers can fine-tune the models using instruction-tuning techniques to adapt them for specific programming tasks or domains. ... -
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Llama 2 Everywhere (L2E)
Llama 2 Everywhere (L2E)
...The project focuses on simplicity and educational clarity by implementing inference for LLaMA-style models in a compact C program rather than relying on large machine learning frameworks. Developers can train models using a Python training pipeline and then run inference using a lightweight C implementation that requires very few dependencies. The architecture mirrors the structure of the LLaMA-2 model family, allowing compatible model checkpoints to be converted and executed within the simplified runtime environment. ... -
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fastquant
Backtest and optimize your ML trading strategies with only 3 lines
...The project focuses on making backtesting accessible by providing a high-level interface that allows users to test investment strategies with only a few lines of code. It integrates historical market data sources and trading frameworks so that users can quickly build experiments without constructing complex data pipelines. The framework enables users to test common strategies such as moving average crossovers, momentum trading, and custom indicators on historical stock data. By automating data retrieval, strategy evaluation, and result visualization, the library reduces the barrier to entry for individuals interested in quantitative finance. ... -
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LLM Applications
A comprehensive guide to building RAG-based LLM applications
...It provides step-by-step guidance for constructing systems that ingest documents, split them into chunks, generate embeddings, index them in vector databases, and retrieve relevant context during inference. The repository also shows how these components can be scaled and deployed using distributed computing frameworks such as Ray. In addition to development workflows, the project includes notebooks, datasets, and evaluation tools that help developers experiment with different retrieval strategies and model configurations. -
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DevOpsGPT
Multi agent system for AI-driven software development
Welcome to the AI Driven Software Development Automation Solution, abbreviated as DevOpsGPT. We combine LLM (Large Language Model) with DevOps tools to convert natural language requirements into working software. This innovative feature greatly improves development efficiency, shortens development cycles, and reduces communication costs, resulting in higher-quality software delivery. The automated software development process significantly reduces delivery time, accelerating software... -
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LangChain Apps on Production with Jina
Langchain Apps on Production with Jina & FastAPI
Jina is an open-source framework for building scalable multi-modal AI apps on Production. LangChain is another open-source framework for building applications powered by LLMs. long-chain-serve helps you deploy your LangChain apps on Jina AI Cloud in a matter of seconds. You can benefit from the scalability and serverless architecture of the cloud without sacrificing the ease and convenience of local development. And if you prefer, you can also deploy your LangChain apps on your own... -
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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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AnyTrading
The most simple, flexible, and comprehensive OpenAI Gym trading
gym-anytrading is an OpenAI Gym-compatible environment designed for developing and testing reinforcement learning algorithms on trading strategies. It simulates trading environments for financial markets, including stocks and forex. -
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D2L.ai
Interactive deep learning book with multi-framework code
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge. This open-source book represents our attempt to make deep learning approachable, teaching you the concepts, the context, and the code. The entire book is drafted in Jupyter notebooks, seamlessly integrating exposition figures, math, and interactive examples with self-contained code. Offers sufficient technical depth to... -
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LLM Cookbook
LLM Introduction Tutorial for Developers, Chinese version
...The project adapts and reproduces content from widely known LLM developer courses and reorganizes it into a structured learning path tailored for developers who want to build real AI applications. It covers the essential topics required to start working with LLM APIs and frameworks, including prompt engineering, application architecture, retrieval-augmented generation, and system evaluation. The repository includes practical coding examples that demonstrate how to integrate language models with tools such as LangChain and other common AI development frameworks. It also provides curated learning modules that guide users from introductory concepts to more advanced topics like building conversational systems or knowledge-based assistants. -
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Lingua-Go
The most accurate natural language detection library for Go
...Other use cases, for instance, might include routing e-mails to the right geographically located customer service department, based on the e-mails' languages. Language detection is often done as part of large machine-learning frameworks or natural language processing applications. In cases where you don't need the full-fledged functionality of those systems or don't want to learn the ropes of those, a small flexible library comes in handy. -
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LLaMA
Inference code for Llama models
“Llama” is the repository from Meta (formerly Facebook/Meta Research) containing the inference code for LLaMA (Large Language Model Meta AI) models. It provides utilities to load pre-trained LLaMA model weights, run inference (text generation, chat, completions), and work with tokenizers. Tokenizer utilities, download scripts, shell helpers to fetch model weights with correct licensing/permissions. Includes example scripts for chat completions and text completions to show how to call the... -
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QuantResearch
Quantitative analysis, strategies and backtests
QuantResearch is a large educational repository dedicated to quantitative finance, algorithmic trading, and financial machine learning research. The project contains numerous notebooks and research materials demonstrating quantitative analysis techniques used in financial markets. These include implementations of factor models, statistical arbitrage strategies, portfolio optimization methods, and reinforcement learning approaches to trading. The repository also explores financial modeling... -
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Consistency Models
Official repo for consistency models
consistency_models is the repository for Consistency Models, a new family of generative models introduced by OpenAI that aim to generate high-quality samples by mapping noise directly into data — circumventing the need for lengthy diffusion chains. It builds on and extends diffusion model frameworks (e.g. based on the guided-diffusion codebase), adding techniques like consistency distillation and consistency training to enable fast, often one-step, sample generation. The repo is implemented in PyTorch and includes support for large-scale experiments on datasets like ImageNet-64 and LSUN variants. It also contains checkpointed models, evaluation scripts, and variants of sampling / editing algorithms described in the paper. ... -
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EasyRL
Reinforcement learning (RL) tutorial series
easy-rl is a beginner-friendly reinforcement learning (RL) tutorial series and framework developed by Datawhale China. It provides educational resources and implementations of various RL algorithms to help new researchers and practitioners learn RL concepts. -
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UniEM
Unified embedding model
UniEM is a unified embedding model designed to create high-quality text embeddings for various natural language processing tasks. -
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SOD
An Embedded Computer Vision & Machine Learning Library
SOD is an embedded, modern cross-platform computer vision and machine learning software library that expose a set of APIs for deep-learning, advanced media analysis & processing including real-time, multi-class object detection and model training on embedded systems with limited computational resource and IoT devices. SOD was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in open source as well as commercial products.... -
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simpleaichat
Python package for easily interfacing with chat apps
...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 validation patterns so your app can reliably parse model outputs instead of wrestling with brittle free-text parsing. The project encourages clean separation between system prompts, user messages, and tool outputs to keep conversations predictable. ...
