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Prasan Yapa's Projects

bert icon bert

TensorFlow code and pre-trained models for BERT

depression_severity_dataset icon depression_severity_dataset

Data for "Early Identification of Depression Severity Levels on Reddit Using Ordinal Classification" paper accepted at The Web Conference '22

eduaid icon eduaid

A tool that can auto-generate short quizzes on the basis of the content provided.

helagrammarly icon helagrammarly

This is a RNN LSTM based online tool to verify Sinhala spellings

helaner icon helaner

This is a Bi-directional LSTM based Nested Named Entity Boundary Recognizer which supports multiple languages including Sinhala

jabref icon jabref

Graphical Java application for managing BibTeX and biblatex (.bib) databases

machine-learning-exams icon machine-learning-exams

This repository contains links to machine learning exams, homework assignments, and exercises that can help you test your understanding.

mental-health icon mental-health

Repository containing code for my internship at Valencia Polytechnic University (summer 2021)

mpc-bert icon mpc-bert

ACL 2021: MPC-BERT: A Pre-Trained Language Model for Multi-Party Conversation Understanding

mpc-bert-2.0 icon mpc-bert-2.0

MPC-BERT-2.0 is an upgraded version which supports for Tensorflow version 2.

parshift icon parshift

Python package based on Gibson's framework (2003) for turn-taking in group conversation analysis.

prompt-in-context-learning icon prompt-in-context-learning

Awesome resources for in-context learning and prompt engineering: Mastery of the LLMs such as ChatGPT, GPT-3, and FlanT5, with up-to-date and cutting-edge updates.

rallylk icon rallylk

A platform for managing motor rallys in Sri Lanka

smartkent icon smartkent

This implementation is a simulation service that is controlled via rest api

snake-ga icon snake-ga

AI Agent that learns how to play Snake with Deep Q-Learning

v4u icon v4u

A platform to navigate the ex-Servicemen to Sri Lankan Community

wsw icon wsw

Who Says What (WSW) is a PLM which models who says what in multi-party conversations to understand equipping discourse parsing in deep semantic structures and contextualized representations of utterances and interlocutors.

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