Text embeddings using pretrainedmodels and OpenAI
In the realm of natural language processing (NLP), the quest for effectively converting textual information into mathematical representations, often referred to as embeddings, has always been paramount. Embeddings allow machines to “understand” and process textual content, bridging the gap between human language and computational tasks. In our previous NLP chapters, we dived deep into the creation of text embeddings and witnessed the transformative power of large language models (LLMs) such as BERT in capturing the nuances of language.
Enter OpenAI, a forefront entity in the field of artificial intelligence research. OpenAI has not only made significant contributions to the LLM landscape but has also provided various tools and engines to foster advancements in embedding technology. In this study, we’re going to embark on a detailed exploration of text embeddings using OpenAI’s offerings.
By embedding...
