is a technique that allows you to answer questions without training a model on a specific question answering task. It works by treating the question answering task as a natural language inference problem, where the model needs to predict whether a given sentence (the question) is entailed by a set of possible answers (the candidate labels).
In this project, I created a simple Python's Flask using the HuggingFace's Transformers library which us a Web application that is answering "What is the capital of a country?".
- Select a country.
- Submit
- Get the capital of the country.
NOTE: The choices of the country are limited to "Canada, Philippines and Tokyo"
- Transformers
- PyTorch