🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.

Minimalist NMT for educational purposes

Based on the Pytorch-Transformers library by HuggingFace. To be used as a starting point for employing Transformer models in text classification tasks. Contains code to easily train BERT, XLNet, RoBERTa, and XLM models for text classification.

Implementation of the paper Video Action Transformer Network

This shows how to fine-tune Bert language model and use PyTorch-transformers for text classififcation

Label data using HuggingFace's transformers and automatically get a prediction service

Instructions for how to convert a BERT Tensorflow model to work with HuggingFace's pytorch-transformers, and spaCy. This walk-through uses DeepPavlov's RuBERT as example.

Utilizing webscraping and state-of-the-art NLP to generate TV show episode summaries.

DistilBERT Question Answering model using SQuAD served with Flask, deployed on Google Cloud Run

Easily deploy a state-of-the-art language model from HuggingFace's Transformers

Determine the polarity of amazon fine food reviews using ULMFiT, BERT, XLNet and RoBERTa

Quora Questions Pair detection with Semantic Similarity

This project used in my dissertation for detecting sarcasm in twitter dataset using Sate-of-the-Art Transformer

machine learning algorithms from scratch