Collections

The Image Segmentation task is an important task in the fields of computer vision and image processing. Its main objective is to segment and classify different regions within an image to delineate the boundaries of objects.

Text Classification is the task of assigning a label or class to a given text. Some use cases are sentiment analysis, natural language inference, and assessing grammatical correctness.

Question Answering models can retrieve the answer to a question from a given text, which is useful for searching for an answer in a document. Some question answering models can generate answers without context!

Task Zero-Shot Image Classification is an important task in the field of image processing and artificial intelligence. This task aims to classify images into different categories where the model has never been trained before.

Image feature extraction is the task of extracting features learnt in a computer vision model.

Audio Classification is the task of assigning a label or class to a given audio. It can be used for recognizing which command a user is giving or the emotion of a statement, as well as identifying a speaker.

Token Classification is a natural language understanding task in which a label is assigned to some tokens in a text. Some popular token classification subtasks are Named Entity Recognition (NER) and Part-of-Speech (PoS) tagging.