Transformers (formerly known as PyTorch-transformers and pytorch-pretrained-bert) provide thousands of pre-trained models to perform tasks on different modalities such as text, vision, and audio.
These models can be applied on:
Text, for tasks like text classification, information extraction, question answering, summarization, translation, text generation, in over 100 languages.
Images, for tasks like image classification, object detection, and segmentation.
Audio, for tasks like speech recognition and audio classification.
Transformer Models are great with Sequential Data and are Pre-trained which makes them versatile and capable. It allows further to Gain Out-of-the-Box Functionality. Transformer models enable you to take a large-scale LM (language model) trained on a massive amount of text (the complete works of Shakespeare), then update the model for a specific conceptual task, far beyond mere “reading,” such as sentiment analysis and even predictive analysis.Who this course is for:Beginner students interested in learning NLP via Transformers
Who this course is for:
Beginner students interested in learning NLP via Transformers
