Aspire Journeys

Introduction to Transformers

  • 4 Courses | 4h 45m
  • 3 Labs | 3h
Rating 5.0 of 1 users Rating 5.0 of 1 users (1)
In this Journey, you will explore transformer models using Hugging Face's transformers library. You will learn the basics of Hugging Face and PyTorch, the different types of transformer models, how they work, how to use them for different language tasks such as text generation, summarization, and sentiment analysis, and how to evaluate the carbon emissions of transformer models.

Track 1: Introduction to Hugging Face

In this track of the Introduction to Transformers Aspire Journey, learn about the Hugging Face AI and machine learning platform and how their tools can streamline ML and AI development.

  • 1 Course | 1h 15m

Track 2: Introduction to PyTorch

In this track of the Introduction to Transformers Aspire Journey, the focus will be on what neural networks are, how to implement them with PyTorch, and how to use them for prediction tasks.

  • 1 Course | 55m
  • 1 Lab | 1h

Track 3: Introduction to Transformers with Hugging Face

In this track of the Introduction to Transformers Aspire Journey, the focus will be on what transformers are, how to perform language tasks like text generation with them, and how to estimate their carbon footprint.

  • 1 Course | 55m
  • 1 Lab | 1h

Track 4: Finetuning Transformer Models

In this track of the Introduction to Transformers Aspire Journey, the focus will be on finetuning transformer models with their own data, including with the cutting-edge techniques of LoRA and quantization.

  • 1 Course | 1h 40m
  • 1 Lab | 1h

EARN A DIGITAL BADGE WHEN YOU COMPLETE THESE TRACKS

Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.

Digital badges are yours to keep, forever.

YOU MIGHT ALSO LIKE

Course Leveraging AI as a Team Member
Rating 4.7 of 21 users Rating 4.7 of 21 users (21)
Book Introduction to Transformers for NLP: With the Hugging Face Library and Models to Solve Problems
Course Attention-based Models and Transformers for Natural Language Processing