Estimating Cost of Embedding with OpenAI API

Embeddings are a powerful tool for natural language processing tasks, but how much do they actually cost? In this video, we'll explore the cost of embedding documents using the OpenAI API. We'll cover everything you need to know, from counting tokens to understanding model pricing, so you can accurately estimate the cost of your embedding projects.

Github Notebook : github.com/technofriends/openai-embeddings/blob/ma…

Blog : mindfulcto.com/from-tokens-to-costs-embedding-esti…

We'll dive deep into:
Counting Tokens: Understand how OpenAI calculates token usage and how it impacts your cost.
Model Pricing: Explore the different embedding models available on OpenAI and their associated costs.
Cost Estimation: Learn how to accurately estimate the total cost of embedding documents using token count and model pricing.
Practical Example: We'll walk through a real-world example of embedding a large dataset of movie titles, demonstrating how to calculate the total cost involved.

Chapters:
00:00 - Introduction to Embeddings and OpenAI API
01:02 - Counting Tokens and Understanding Their Impact on Cost
02:46 - Exploring OpenAI Embedding Model Pricing
04:47 - Calculating Total Tokens for a Large Dataset
06:11 - Estimating the Total Cost of Embedding Your Documents
09:59 - Generating a Large Movie Dataset for Embedding
12:19 - Calculating Total Cost for Embedding the Movie Dataset
By the end of this video, you'll be able to confidently estimate the cost of using OpenAI's embedding models for your NLP projects.

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