Open-source alternatives to VaderSentiment

This is a Chinese natural language processing toolkit providing a suite of tools for word segmentation, part-of-speech tagging, and named entity recognition. It includes a neural dependency parser for analyzing syntactic and semantic relationships between words and a machine learning training suite for creating custom linguistic models using annotated datasets. The toolkit distinguishes itself through its deployment flexibility, offering a dockerized server and a web service interface that exposes processing capabilities via API. It supports the use of pretrained models and allows for the int

Spark NLP is a toolkit for scalable text analysis and machine learning built on the Apache Spark distributed computing framework. It provides a multimodal machine learning framework and a distributed pipeline system for sequencing annotators to process large-scale linguistic data. The library includes a transformer text processor for generating contextual vector embeddings and a dedicated inference engine for managing large language models. The project distinguishes itself through its ability to process heterogeneous data types, including text, audio, and images, within a unified vision-langu

SnowNLP is a Python library for Chinese natural language processing. It provides tools for text segmentation, sentiment analysis, document classification, and phonetic transliteration. The library includes capabilities for training and saving custom machine learning models for tokenization and sentiment analysis using raw training datasets. It covers a range of linguistic processing areas, including parts of speech tagging, sentence splitting, and text similarity measurement. The toolkit also provides utilities for extracting key information through text summarization and calculating word im

trump2cash is a sentiment-based stock trading bot and social media market monitor. It uses a natural language processing sentiment analysis tool to scan real-time social media feeds for mentions of publicly traded companies and translates the emotional tone of that text into automated buy or short stock market orders. The system utilizes a ticker mapping utility to resolve company names, subsidiaries, and brands into valid public stock market ticker symbols. To verify the efficacy of these sentiment-driven signals, it includes an algorithmic trading backtester that evaluates trading strategie

This project serves as an educational resource and guide for prompt engineering, providing a structured methodology for interacting with large language models. It focuses on teaching core strategies to improve the reliability, accuracy, and consistency of model outputs across a variety of natural language processing tasks. The framework emphasizes the use of standardized templates and logical decomposition to manage complex instructions. By implementing techniques such as few-shot context injection, iterative refinement, and delimiter-based segmentation, the project demonstrates how to guide

WeiboSpider is a social media scraper designed to extract user profiles, posts, and interaction data from the Sina Weibo platform. It functions as a web-based data crawler that retrieves information via external interfaces rather than parsing the visual frontend. The tool includes a content lineage tracer to follow shared posts back to their original sources. It also features a social engagement analyzer to collect view counts and nested comment threads to measure user interaction metrics. The system provides capabilities for keyword-based social monitoring and search result filtering to tra

This project is a Sina Weibo web scraper and social media data pipeline designed to extract user profiles, posts, comments, and multimedia assets. It functions as a containerized data crawler that automates the collection and local storage of social media content and engagement metrics. The system includes a processing layer that uses large language models to analyze scraped text, generating summaries and sentiment analysis. It differentiates itself through a deployment-ready container model featuring an HTTP interface for managing extraction tasks and monitoring job progress. The crawler co

Multilingual text (NLP) processing toolkit

Chat with your favourite LLaMA models in a native macOS app

This project is a quantized fine-tuning framework for large language models. It implements a low-rank adaptation library and a four-bit quantizer to reduce the GPU memory requirements needed to train large models. The framework utilizes four-bit quantization and low-rank adapters to enable model training on consumer-grade hardware. It further reduces the memory footprint through double quantization and a paged optimizer that offloads states to system RAM. The system supports distributed training across multiple GPUs to handle larger parameter scales and includes utilities for custom dataset

AudioGPT is an LLM-driven audio framework and processing suite that uses large language models to orchestrate neural audio pipelines. It functions as a multimodal audio generator and processing system, integrating a collection of pretrained models to handle speech synthesis, sound generation, and audio manipulation. The system is distinguished by its ability to generate audio from diverse inputs, including text and images, and its capacity to produce synchronized talking head videos. It also operates as a neural speech translator, converting spoken language between different tongues while pre

Gibran is an Elixir natural language processor, and a port of WordsCounted.

Simple sentiment analysis with Ruby

ChatALL is a desktop application that functions as a multi-model chat client and aggregator for artificial intelligence services. It enables users to send a single prompt to multiple AI models simultaneously, allowing for the side-by-side comparison of generated responses within a unified interface. The application distinguishes itself through a local-first approach to data management, ensuring that all conversation logs and user configurations are stored directly on the user's device. This architecture supports privacy and offline access while providing a centralized system for managing and

AllenNLP is a PyTorch-based research library and deep learning language toolkit designed for developing and training neural network architectures for linguistic tasks. It provides a distributed training system that coordinates data and gradients across multiple GPUs and a framework for integrating pretrained transformer architectures. The system distinguishes itself with a dedicated algorithmic bias mitigation tool used to identify and reduce bias in linguistic model predictions. It also includes model influence analysis to interpret predictions by calculating the influence of specific traini

OpenHands is an autonomous AI software engineer and coding assistant designed to execute software engineering tasks by interacting directly with codebases and development environments. It functions as a platform for running AI agents that can write code and manage files to automate complex development workflows. The system distinguishes itself through a container-based execution environment that isolates agent actions within a sandboxed Linux environment. It employs an autonomous agent loop of observation, planning, and action, supported by a standardized communication protocol that allows it

MultimodalC4 is a multimodal extension of c4 that interleaves millions of images with text.

This repository contains custom pipes and models related to using spaCy for scientific documents.

Summary of Responses to Questionnaire on Annotation Platform https://forms.gle/iZk8kehkjAWmB8xe9

This repository consists of all my NLP Projects

DocsGPT is a retrieval-augmented generation platform and private knowledge base used to build AI agents that perform grounded search and analysis. It functions as a multi-model AI orchestrator and enterprise agent builder, allowing for the integration of various local and cloud language models to customize reasoning and text generation. The project provides a visual environment for developing automated assistants using conditional logic and third-party API connectivity. It enables the creation of private AI agents capable of performing enterprise search and detailed document analysis using pr

Argilla is a collaborative AI feedback tool and data curation management system. It serves as a human-in-the-loop dataset platform designed to coordinate workforce annotators and domain experts in labeling, rating, and refining data samples for machine learning projects. The platform focuses on large language model dataset curation and reinforcement learning from human feedback workflows. It provides a shared workspace for integrating human expertise into AI development to validate model outputs and correct data errors. The system manages the end-to-end machine learning data pipeline, includ

Implementation of various topic models

lecture notes for probabilistic topic models using ipython notebook

Natural language detection library for Go