Denis2054/Transformers-for-NLP-2nd-Edition
Companion code repository for a book covering transformer models from BERT to GPT-4, including fine-tuning, training, prompt engineering, and OpenAI API examples.
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This repository contains Jupyter Notebook examples demonstrating how to work with transformer models for NLP tasks. It covers fine-tuning and training with Hugging Face Transformers, using OpenAI APIs (GPT-3.5-turbo, GPT-4), generating images with DALL-E 2, and advanced prompt engineering techniques. The material ranges from foundational models like BERT and RoBERTa through to multimodal capabilities including speech-to-text and text-to-image generation.
Frequently asked
- What is Denis2054/Transformers-for-NLP-2nd-Edition?
- Companion code repository for a book covering transformer models from BERT to GPT-4, including fine-tuning, training, prompt engineering, and OpenAI API examples.
- Is Transformers-for-NLP-2nd-Edition open source?
- Yes — Denis2054/Transformers-for-NLP-2nd-Edition is open source, released under the MIT license.
- What language is Transformers-for-NLP-2nd-Edition written in?
- Denis2054/Transformers-for-NLP-2nd-Edition is primarily written in Jupyter Notebook.
- How popular is Transformers-for-NLP-2nd-Edition?
- Denis2054/Transformers-for-NLP-2nd-Edition has 965 stars on GitHub.
- Where can I find Transformers-for-NLP-2nd-Edition?
- Denis2054/Transformers-for-NLP-2nd-Edition is on GitHub at https://github.com/Denis2054/Transformers-for-NLP-2nd-Edition.