Embeddings vs Fine-Tuning - Part 1: Understanding and Implementing Embeddings
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Dive into a comprehensive 31-minute video tutorial on embeddings in natural language processing. Learn the fundamentals of semantic search, how to effectively use embeddings with language models, and explore key concepts like cosine similarity and dot product similarity. Discover practical techniques for embedding datasets, preparing data, and chunking for optimal results. Gain insights into selecting appropriate embedding lengths and implementing Llama 2 13B with GPTQ in Google Colab. Compare various embedding options, including OpenAI and SBERT, and master the process of creating embeddings from data. Evaluate embedding performance using ChatGPT and analyze results with Llama 13-B and GPT-4. Conclude with expert tips for enhancing embedding performance, including the ColBERT approach, to maximize the potential of embeddings in language model applications.