All Collections
Task Text-to-Image is an important task in the field of artificial intelligence and natural language processing. This task aims to create images from descriptions or descriptive text.
The Image-to-Text task is an important task in the field of natural language processing and computer vision. Its purpose is to convert information within an image into readable and understandable text.
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.
The Object Detection task is an important task in the fields of computer vision and artificial intelligence. Its main objective is to detect and determine the position of objects within images or videos.
The DQA is a task in natural language processing and information retrieval that focuses on automatically generating accurate and relevant answers to questions based on a given document.
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.
Image-to-Image is an important task in the field of image processing, where we convert images from one format or data type to another.
Task Text Generation is an important task in the field of natural language processing and artificial intelligence. This task aims to generate text automatically from input data, including descriptions, stories, articles, or other types of text.
Text2Text Generation is a versatile and powerful approach in Natural Language Processing (NLP) that involves transforming one piece of text into another. This can include tasks such as translation, summarization, question answering, and more.
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!
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.
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.
Depth Estimation is the task of predicting depth of the objects present in an image.
Image feature extraction is the task of extracting features learnt in a computer vision model.
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.
This is a natural language processing task where a model is trained on labeled data but can classify new examples from classes it has never encountered before.
Image Classification is the task of assigning a label or class to an entire image. Images are expected to have only one class for each image. Image classification models take an image as input and return a prediction about which class the image belongs to