Skip to content

Latest commit

 

History

History
117 lines (87 loc) · 3.87 KB

README.md

File metadata and controls

117 lines (87 loc) · 3.87 KB
Raw

Status GitHub Issues GitHub Pull requests Languages


Logo

BLOOMingWave

Laveraging the power of Large Language Models
Explore the docs »

View Demo · Report Bug · Request Feature


Demo
Demo

Table of Contents

Introduction

H2O Wave is a software stack for building beautiful, low-latency, real-time, browser-based applications and dashboards entirely in Python without using HTML, Javascript, or CSS. Using the framework, we can develop any kind of a business application or any data science related application. In this project, I created an application to use as a playground to use BLOOM models with a higher granularity than in huggingface to do several NLP tasks by prompt tuning. Enjoy !!!

System Requirements

  • Python
  • pip
  • GIT

Prerequisite

In order to use the application, you need to have a huggingface access token with read access. Follow the guide in here.

Quick Start

H2O Wave Installation

  1. Download and extract the H2O Wave SDK for your platform using - https://github.com/h2oai/wave/releases/tag/v0.19.0
  2. Move it to a location of interest. ($HOME/wave/)
  3. Go to your Wave directory and open a new terminal. Start the wave server using,
./waved

Step-By-Step guide can also be found here.

Setting Up the project

  1. Clone the repository and go inside the folder.
git clone https://github.com/sakunaharinda/BLOOMing-Wave.git
cd BLOOMing-Wave
  1. Set up the virtual environment
 python3 -m venv venv
 source venv/bin/activate
  1. Install the dependancies
pip install -r requirements.txt

Run the application

  1. Run the application using the following command
wave run app.app
  1. Then visit localhost:10101
  2. Enjoy playing with BLOOM !!

Upcoming Features

New Chatbot, Sentiment Analysis, Summerization and many other features will be introduced soon !! 🤗

Acknowledgements