This series of notebooks is aimed at helping fellow NLP/ML enthusiasts quickly build web apps using the Gradio and transformers libraries.
Notebook1.0: I start with one of the simplest examples possible — building a web app for sentiment analysis using Hugging Face’s pipeline API.
Notebook1.1: Gradio works just as well with pickled models via scikit-learn and joblib. This notebook demos a quick deployment of a trained Logistic Regression classifier for troll-Vs-real tweets.
Notebook2.0: Demo web app to compare the summarization capabilities of two different models: FB’s Bart and Google’s Pegasus. This is a great way to directly compare the results from multiple models without having to copy out the results from different apps, or switch screens back and forth between two models.
Notebook3.0: Demo web app for connecting models of different functionalities under one Gradio app, in this case a translator-summarizer that takes in Chinese text and produces a summary of the English translation.
Notebook4.0: Demo speech-to-text app that takes in audio clips and returns a text transcript.
More details in this Medium post.