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Fine-tune LLM on your dialog history, run chatbot as it will be you

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Textual Avatar

Welcome to the Textual Avatar project! This repository contains a minimal yet comprehensive code snippet that guides you through the process of creating your own personalized conversational AI using a fine-tuned language model (LLama-2 as of August 2023).

Project Overview

Have you ever wondered what it would be like to have a chatbot that responds in a way that's uniquely yours? With Textual Avatar, you can achieve just that. This project takes you through the following steps:

  1. Extract Text Data: Learn how to extract your own text data from various sources.
  2. Conversion and Encryption: Convert your data into an instruction-based format and ensure your privacy by encrypting it.
  3. Fine-Tune LLM: Fine-tune the LLama-2 language model using your encrypted data for a personalized touch.
  4. Try the Demos: Explore the provided inference demos, including a user-friendly Gradio interface and a Telegram bot.

Getting Started

To get started, simply open the textual_avatar.ipynb notebook in this repository. This notebook serves as your guide, providing step-by-step instructions, code snippets, and explanations to help you create your own Textual Avatar.

Got questions or ideas on improvement? Feel free to reach out. [email protected]

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Fine-tune LLM on your dialog history, run chatbot as it will be you

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