Basic Understanding Token Usage, Pricing, and Parameters for GPT Language Models

Tokens:

When using text-based models like GPT, input text is split into tokens for processing. For instance, the sentence "I enjoy reading books" would be tokenized into individual units like "I," "enjoy," "reading," and "books." Each token typically consists of 4 English characters.

Example: Input Text: "I enjoy reading books"

Tokens: ["I", "enjoy", "reading", "books"]Pricing for these models is based on the number of tokens processed. OpenAI charges based on the total input and output tokens generated during interactions with the model.

 

How to Specify Token Count in API Response:

When interacting with an API, you can specify the number of tokens you want in the response using the max_tokens parameter. For example, setting max_tokens=20 would request a response containing up to 20 tokens.

 

Example:

API Request: Generate a summary of a book with max_tokens=20

The API would then provide a response with a summary containing a maximum of 20 tokens.

 

Managing Stop Sequences:

Stop sequences are used to control when the model should stop generating output. For instance, if you set stop_sequence=5 when asking for a list of movies, the model would naturally stop after listing 4 movies.

Example:

Request: Generate a list of popular movies with stop_sequence=5

  • Output: The Shawshank Redemption
  • Inception
  • The Godfather
  • Pulp Fiction

 

The model stops after listing 4 movies due to the specified stop sequence.

 

Echo and N Parameters:

The n parameter is useful when you want responses split into smaller segments for easier processing. Echo, on the other hand, includes previous prompts in the completion to maintain context.

 

Example:

Prompt:

 User: Hi

Chatbot: Hello! How can I assist you today? Setting n=3 would split the chatbot's response into parts for easier handling:

  •  "Hello!"
  • "How can I assist you today?"

 

Enabling echo ensures that previous interactions are included in subsequent responses without affecting token pricing. echo="True"

 

Token Pricing for Different Models:

Different models have varying token pricing structures based on their capabilities and performance levels.


  • Text-Davinci-003: $0.02 per 1k tokens
  • Text-Curie-001: $0.002 per 1k tokens
  • GPT-3.5 Turbo: $0.002 per 1k tokens

 

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