2nd Kaggle competition 04/2020

Language Detection using DistilBERT

Notebook on finetuning BERT

NLP Sentiment classifier using pretrained BERT

PyTorch Transformer-based Language Model Implementation of ConceptSHAP

Predict short and long answer responses to real questions about Wikipedia articles.

Sentiment analysis on product reviews with identification of most reviewed products from Amazon product reviews dataset consists of 35000 reviews.

Text summarization of Hotel reviews using Huggingface Transformers T5 and Bart

BERT with the huggingface PyTorch library on CoLA dataset for sentence classification and evaluate predictions using Matthew's correlation coefficient

Chatbot that can emulate someone's chatting style by looking at their LINE chat logs. Uses transfer learning on GPT-2 using the Hugging Face model. Can be interacted with using discord.

Embeddings projections using TensorFlow Projector and HuggingFace Transformers

In this project, we will take analyze positive and negative hotel reviews and design a model for inferring positive or negative sentiment given a review. We combine a pretrained BERT lanuguage model and a custom multi-layer perceptron to achieve this.

End-to-End NER for BERT variants

Deploy PhoBERT for Abstractive Text Summarization as REST API using StreamLit, Transformers by Hugging Face and PyTorch

This project is used to generate a blog post using Natural Language processing, Hugging Face Transformers and GPT-2 Model.

Sentiment Analysis with HuggingFace Transformers Pipeline with 5 Lines of Python code

Generate summaries from texts using Streamlit & HuggingFace Pipeline

The chosen task is a multi-class text classification on Movie Reviews. For each text movie review, the model has to predict a label for the sentiment. We evaluate the outputs of the model on classification accuracy. The sentiment labels are: 0 → Negative 1 → Somewhat negative 2 → Neutral 3 → Somewhat positive 4 → Positive. This movie review data…

Tigrinya corpus data, resources for NLP training

Tutorial on using Hugging Face's Vision Transformers for Image Classification