Transformers for Natural Language Processing and Computer Vision
Explore Generative AI and Large Language Models with Hugging Face, ChatGPT, GPT-4V, and DALL-E 3
Created by Denis Rothman
Explore how transformer models are powering breakthroughs in natural language processing and computer vision. Get hands-on with leading platforms and learn to build, fine-tune, and apply generative AI models for real-world tasks. Understand both the opportunities and challenges of working with large language models.
Packt | Feb 2024 | 730 min
What You Will Learn
You will develop practical skills by working through real examples that cover pretraining, fine-tuning, and deploying transformer models. Step-by-step projects help you apply concepts to tasks like summarization, question answering, and image classification. Along the way, you will explore different platforms and learn best practices for safe and effective AI development.
Key Features
- Build and fine-tune transformer models for NLP and computer vision tasks
- Apply retrieval augmented generation to improve accuracy and control outputs
- Identify and mitigate risks like hallucinations using moderation and rule-based tools
Target Audience
Designed for engineers, data scientists, and developers with some Python and machine learning experience who want to deepen their understanding of transformers and generative AI. If you are looking to apply large language models in NLP or computer vision, or want to keep up with the latest AI trends, you will find practical guidance and actionable techniques here.
