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This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

Easily integrate Large Language Models into your Python code. Simply use the `@prompt` and `@chatprompt` decorators to create functions that return structured output from the LLM. Mix LLM queries and function calling with regular Python code to create complex logic.

Awesome LLM compression research papers and tools to accelerate LLM training and inference.

The 'machine-learning-research' repository is a comprehensive collection of resources related to mathematics, machine learning, deep learning, artificial intelligence, data science, and various scientific fields. It includes materials such as courses, tutorials, books, podcasts, communities, online courses, papers, and dissertations. The repository covers topics ranging from fundamental math skills to advanced machine learning concepts, with a focus on applications in healthcare, genetics, computational biology, precision health, and AI in science. It serves as a valuable resource for individuals interested in learning and researching in the fields of machine learning and related disciplines.

This repository is dedicated to the pruning of large language models (LLMs). It aims to serve as a comprehensive resource for researchers and practitioners interested in the efficient reduction of model size while maintaining or enhancing performance. The repository contains various papers, summaries, and links related to different pruning approaches for LLMs, along with author information and publication details. It covers a wide range of topics such as structured pruning, unstructured pruning, semi-structured pruning, and benchmarking methods. Researchers and practitioners can explore different pruning techniques, understand their implications, and access relevant resources for further study and implementation.

Bagatur chess engine is a powerful Java chess engine that can run on Android devices and desktop computers. It supports the UCI protocol and can be easily integrated into chess programs with user interfaces. The engine is available for download on various platforms and has advanced features like SMP (multicore) support and NNUE evaluation function. Bagatur also includes syzygy endgame tablebases and offers various UCI options for customization. The project started as a personal challenge to create a chess program that could defeat a friend, leading to years of development and improvements.

The 'awesome-AI4MolConformation-MD' repository focuses on protein conformations and molecular dynamics using generative artificial intelligence and deep learning. It provides resources, reviews, datasets, packages, and tools related to AI-driven molecular dynamics simulations. The repository covers a wide range of topics such as neural networks potentials, force fields, AI engines/frameworks, trajectory analysis, visualization tools, and various AI-based models for protein conformational sampling. It serves as a comprehensive guide for researchers and practitioners interested in leveraging AI for studying molecular structures and dynamics.

Aiwnios is a HolyC Compiler/Runtime designed for 64-bit ARM, RISCV, and x86 machines, including Apple M1 Macs, with plans for supporting other architectures in the future. The project is currently a work in progress, with regular updates and improvements planned. Aiwnios includes a sockets API (currently tested on FreeBSD) and a HolyC assembler accessible through AARCH64. The heart of Aiwnios lies in `arm_backend.c`, where the compiler is located, and a powerful AARCH64 assembler in `arm64_asm.c`. The compiler uses reverse Polish notation and statements are reversed. The developer manual is intended for developers working on the C side, providing detailed explanations of the source code.

Airchains is a tool for setting up a local EVM network for testing and development purposes. It provides step-by-step instructions for installing and configuring the necessary components. The tool helps users create their own local EVM network, manage keys, deploy contracts, and interact with the network using RPC. It also guides users on setting up a station for tracking and managing transactions. Airchains is designed to facilitate testing and development activities related to blockchain applications built on the EVM platform.

CISO Assistant is a tool that helps organizations manage their cybersecurity posture and compliance. It provides a centralized platform for managing security controls, threats, and risks. CISO Assistant also includes a library of pre-built frameworks and tools to help organizations quickly and easily implement best practices.

Domino is an open source workflow management platform that provides an intuitive GUI for creating, editing, and monitoring workflows. It also offers a standard way of writing and publishing functional pieces that can be reused in multiple workflows. Domino is powered by Apache Airflow for top-tier workflows scheduling and monitoring.

The AI-Gateway repository explores the AI Gateway pattern through a series of experimental labs, focusing on Azure API Management for handling AI services APIs. The labs provide step-by-step instructions using Jupyter notebooks with Python scripts, Bicep files, and APIM policies. The goal is to accelerate experimentation of advanced use cases and pave the way for further innovation in the rapidly evolving field of AI. The repository also includes a Mock Server to mimic the behavior of the OpenAI API for testing and development purposes.

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