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Adds notebook for Cost efficient NLP #1114

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Summary

This PR introduces a cookbook that provides guidance on performing fundamental NLP tasks in a cost-efficient manner.

Motivation

Over the past few years, developers have encountered significant challenges when dealing with text data, despite the availability of rich resources such as SpaCy and other NLP libraries. These challenges persist due to the constantly increasing volume of data, which demands considerable human involvement, thought, and effort.

Large language models (LLMs), are changing the way we handle text data. LLMs can analyze text data much faster than humans and can understand it in a way that's similar to how we do. So why not leverage their advantages for NLP tasks?


For new content

When contributing new content, read through our contribution guidelines, and mark the following action items as completed:

  • I have added a new entry in registry.yaml (and, optionally, in authors.yaml) so that my content renders on the cookbook website.
  • I have conducted a self-review of my content based on the contribution guidelines:
    • Relevance: This content is related to building with OpenAI technologies and is useful to others.
    • Uniqueness: I have searched for related examples in the OpenAI Cookbook, and verified that my content offers new insights or unique information compared to existing documentation.
    • Spelling and Grammar: I have checked for spelling or grammatical mistakes.
    • Clarity: I have done a final read-through and verified that my submission is well-organized and easy to understand.
    • Correctness: The information I include is correct and all of my code executes successfully.
    • Completeness: I have explained everything fully, including all necessary references and citations.

We will rate each of these areas on a scale from 1 to 4, and will only accept contributions that score 3 or higher on all areas. Refer to our contribution guidelines for more details.

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