AI Q&A

Chat With Your Docs is a Python application that allows users to chat with multiple document formats such as PDFs, web pages, and YouTube videos. Users can ask questions using natural language and the application will provide relevant answers based on the document content. The app uses language models to generate accurate answers. Note that the app only responds to questions related to loaded documents.

Llama3-ChatQA-1.5-70B is an advanced conversational question answering and retrieval enhanced generation (RAG) model developed by NVIDIA. The model is based on the Llama-3 base model and uses an improved training method that specifically enhances tabular and arithmetic computing capabilities. It has two variants: Llama3-ChatQA-1.5-8B and Llama3-ChatQA-1.5-70B. The model achieves excellent results on multiple conversational Q&A benchmarks, demonstrating its efficient ability to handle complex conversations and generate relevant answers.

Llama3-ChatQA-1.5-8B is an advanced conversational question answering and retrieval augmented generation (RAG) model developed by NVIDIA. This model improves on ChatQA (1.0) by adding conversational question and answer data to enhance its tabular and arithmetic computing capabilities. It has two variants: Llama3-ChatQA-1.5-8B and Llama3-ChatQA-1.5-70B, both trained using Megatron-LM and then converted to Hugging Face format. The model performs well on the ChatRAG Benchmark and is suitable for scenarios requiring complex dialogue understanding and generation.

ChatQA is a family of conversational question answering (QA) models that can achieve GPT-4 level accuracy. We propose a two-stage guided tuning method that can significantly improve zero-shot dialogue QA results for large language models (LLMs). To handle retrieval in conversational QA, we fine-tune a dense retriever on a multi-round QA dataset, which provides comparable results to using state-of-the-art query rewriting models while significantly reducing deployment costs. Notably, our ChatQA-70B can outperform GPT-4 (54.14 vs. 53.90) on average scores on 10 conversational QA datasets without relying on any synthetic data from the OpenAI GPT model.

Perplexity Copilot leverages powerful AI models like GPT-4 and Claude 2 to provide in-depth answers. It talks to you, asks questions and listens, constantly adapting and refining search results to your exact needs to provide answers that fit your needs.

This plug-in was developed by students to help answer various surveys. Through an interactive pop-up window, the plugin uses your API key and the AI ​​model of choice to provide accurate and fast answers. It acts as a real-time smart assistant tool.

Poe is an app that lets you ask questions, get answers instantly, and have conversations with AI. It offers a wealth of features and pricing options that enable you to customize your chat experience.