Denis2054/Transformers-for-NLP-2nd-Edition
Transformer models from BERT to GPT-4, environments from Hugging Face to OpenAI. Fine-tuning, training, and prompt engineering examples. A bonus section with ChatGPT, GPT-3.5-turbo, GPT-4, and DALL-E including jump starting GPT-4, speech-to-text, text-to-speech, text to image generation with DALL-E, Google Cloud AI,HuggingGPT, and more
This project provides practical examples and code for working with large language models, from traditional Transformer architectures like BERT to advanced models such as GPT-4 and DALL-E. It helps data scientists and AI engineers understand how to use and customize these models for tasks like fine-tuning, training, and prompt engineering, turning raw text or speech into structured information or generated content.
957 stars. No commits in the last 6 months.
Use this if you are a data scientist or AI engineer looking for hands-on, executable code examples to learn and apply Transformer models for various NLP and generation tasks.
Not ideal if you are looking for a simple, plug-and-play API to integrate AI into an existing application without diving into model specifics or code.
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MIT
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Jan 04, 2024
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