a mini zero-shot text classification implementation using streamlit and transformers

An approach to extracting and summarizing key infrastructure and community impact information from wind disaster reconnaissance reports using Zero-shot text classification with BART-large models, highlighted by keywords.

Transformers, including the T5 and MarianMT, enabled effective understanding and generating complex programming codes. Consequently, they can help us in Data Security field. Let's see how!

The goal here is to develop a simple mock web app book library for demonstrating a possible use of AI for aiding users

LLMs for Low Resource Languages in Multilingual, Multimodal and Dialectal Settings

Comparing zero-shot and fine-tuned text classification transformer models across different review datasets

The source code used for paper "PIEClass: Weakly-Supervised Text Classification with Prompting and Noise-Robust Iterative Ensemble Training", published in EMNLP 2023.

Code for EMNLP2019 paper : "Benchmarking zero-shot text classification: datasets, evaluation and entailment approach"

Named Entity Recognition to detect landmarks in German texts

Applying zero-shot learning on classification task.

Generalized Zero-Shot Character Recognition

Trying out with HuggingFace Models

Repository with the source code of our experiments for a multi-objective prioritization approach to optimize the execution of natural language test cases of a game.

Exploring fast & accurate zero-shot text classification

Various NLP tasks for Global Health Analysis, including an automatic Named Entity Recognition (NER) pipeline to annotate Global Digital Health Documents.

This repository is dedicated to a TIL project i.e. text classification project where we aim to build a robust and accurate text/article classification model according to IAB Categories.

BioCLIP base model for use with Autodistill.

some useful colab files

FastViT base model for use with Autodistill.

For NYC GAI/LLM Hackathon.