A Scalable and Explainable Approach to Discriminating Between Human and Artificially Generated Text

Text Generator is a versatile plugin for Obsidian that allows you to generate text content using various AI providers, including OpenAI, Anthropic, Google and local models.

Open-source ecosystem for building AI-powered conversational solutions using RAG, agents, FSMs, and LLMs.

🔍 LangKit: An open-source toolkit for monitoring Large Language Models (LLMs). 📚 Extracts signals from prompts & responses, ensuring safety & security. 🛡️ Features include text quality, relevance metrics, & sentiment analysis. 📊 A comprehensive tool for LLM observability. 👀

🐶 Data for AmbigNLG: Addressing Task Ambiguity in Instruction for NLG (Ayana Niwa and Hayate Iso; EMNLP 2024)

Encoder-Decoder zero shot domain (skill), intent, and entity tagging NLU model with a zero-shot NLG for generating voice assistant responses. All in one!

Papers and Book to look at when starting AGI 📚

Evaluation code for various unsupervised automated metrics for Natural Language Generation.

A Repo to store the Google Colaboratory Notebooks that I have created and shared

An Annoying Kuriboh Discord Bot.

中文文本生成（NLG）之文本摘要（text summarization）工具包, 语料数据(corpus data), 抽取式摘要 Extractive text summary of Lead3、keyword、textrank、text teaser、word significance、LDA、LSI、NMF。（graph，feature，topic model，summarize tool or tookit）

Transformer Balance Research

Customized Pretraining for NLG Tasks

The PyTorch implementation of fine-tuning the GPT-2(Generative Pre-trained Transformer 2) for dialogue generation.

Implementation of ChatGPT RLHF (Reinforcement Learning with Human Feedback) on any generation model in huggingface's transformer (blommz-176B/bloom/gpt/bart/T5/MetaICL)

Knowledge-bound counter speech generation to challenge hate speech

This repository contains the collection of explorative notebooks pure in python and in the language that we, humans can read. Have tried to compile all lectures from the Andrej Karpathy's 💎 playlist on Neural Networks - which we will end up with building GPT.

Neural question generation using transformers