The objective of this challenge is to develop a machine learning model to assess if a twitter post that is related to vaccinations is positive, neutral, or negative.

The main goal of this repository is to obtain the phrases or words from a given sentence which strongly agree to the corresponding sentiment

Models to detect hateful comments served with flask trained on Kaggle's Toxic Comment Classification Challenge dataset.

Implementation of state-of-the-art NLP models on downstream tasks

Text summarization of Hotel reviews using Huggingface Transformers T5 and Bart

The solution of Kaggle problem: Google QUEST Q-A Labeling https://www.kaggle.com/c/google-quest-challenge

Custom word embeddings created from latent features generated by gensim and hugging face models

Tutorial on Hugging Face transformers

BERT inference (with similar function to hanxiao/bert-as-service) for spaCy with custom extension attributes

The objective of this challenge is to develop a machine learning model that classifies statements and questions expressed by university students in Kenya when speaking about the mental health challenges they struggle with. The four categories are depression, suicide, alchoholism, and drug abuse.

Training the Bidirectional Encoder Representations from Transformers (BERT) model for natural language understanding tasks.

This repository contains my notebooks for the Kaggle challenge "Real or Not? NLP with Disaster Tweets"

Text-based AI training and generation with the aitextgen package using OpenAI's GPT-2 architecture.

Генератор всякого на основе предобученной GPT2

This is the second part of the Deep Learning Course for the Master in High-Performance Computing (SISSA/ICTP).)

State-of-the-art question answering with HuggingFace and Streamlit

The contributions/pull repo for smoketrees model zoo

Sentiment-analysis on Google Play app reviews using Bert

Question answering system with transformers

Twitter Sentiment Extraction using Custom Roberta Transformer Model and using Pre-trained model weights for prediction