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Prompt Engineering Guide
  • Prompt Engineering Guide
  • Introduction
    • Introduction
    • What is an LLM
    • Soekia - What is an LLM
    • ChatGPT Models
    • What is a prompt?
    • Prompt Categories
    • Good prompting
    • Misconceptions about LLM's
  • Configuring ChatGPT
    • ChatGPT Configuration
  • Text Prompts
    • Prompt Frameworks
    • Roles
    • Prompt Cheat Sheet
    • Output Formats
    • Copy of Output Formats
    • Prompt Techniques
    • Prompt Refinement
    • Prompt Patterns
    • Temperature Parameter
  • Custom GPTs
    • Introduction to Custom GPTs
    • The GPT Store
    • Step-by-Step Guide to Creating a Custom GPT
    • Testing and Refining Your Custom GPT
    • Use Cases
    • TASKS
    • Scheduled Tasks
  • Appendix
    • Prompting Terms
    • About
    • Chorus
  • References
  • Hack and Track
  • FAQ
  • GPT4o Announcement
  • Exercises
    • Excercise: Geopandas
  • Group 1
    • Projekte
  • Write like me
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On this page
  • How does model learning in custom gpts in chatgpt work exactly?
  • What File types are foreseen in openai custom gpt?
  • What are maximum sizes in number of files and file size limits
  • What is a token and how can it be calculated?
  • What is a token and how can it be calculated?

FAQ

How does model learning in custom gpts in chatgpt work exactly?

Custom GPTs in ChatGPT do not actually perform any model learning or training. They are pre-configured AI assistants that leverage OpenAI's existing language models, such as GPT-3 or GPT-4, to provide specialized capabilities[1][3].

The process of creating a Custom GPT involves:

  1. Defining the purpose, instructions, and capabilities of the AI assistant using natural language prompts[2][3]

  2. Optionally providing additional knowledge sources, such as documents or datasets, to enhance the GPT's expertise in a particular domain[2]

  3. Configuring the GPT's abilities, such as web browsing, image generation, or code execution[3]

However, the underlying language model itself is not retrained or fine-tuned when creating a Custom GPT. The model's parameters remain fixed, and the GPT's specialized behavior is achieved through carefully crafted instructions and prompts[2][3].

In summary, Custom GPTs in ChatGPT provide a user-friendly interface to leverage pre-trained language models for specific use cases, without requiring any actual model training or learning on the user's part.

Quellen [1] ChatGPT Custom GPT Models: Tailoring AI for Specific Needs https://fastbots.ai/blog/chatgpt-custom-gpt-models-tailoring-ai-for-specific-needs [2] How to create custom GPTs in ChatGPT - Pluralsight https://www.pluralsight.com/resources/blog/data/how-create-custom-gpts-chatgpt [3] How to Make Custom ChatGPT Models: 5 Easy Steps to ... - DataCamp https://www.datacamp.com/tutorial/how-to-make-custom-gpts [4] Introducing GPTs - OpenAI https://openai.com/blog/introducing-gpts

What File types are foreseen in openai custom gpt?

According to the search results, OpenAI Custom GPTs support a variety of file types for knowledge sources and file uploads:

  1. Knowledge sources can include many file types, such as PDF, text, CSV, and other data formats[1][2]. These files are used to extend the GPT's knowledge with domain-specific information.

  2. For file uploads, all common file extensions for text files, spreadsheets, presentations, and documents are supported[3]. The maximum file size is 512MB per file, with a 2M token limit for text and document files (this limitation does not apply to spreadsheets)[3].

  3. Images can also be uploaded, with a size limit of 20MB per image[3]. However, images embedded in documents or presentations are not yet supported[3].

  4. Files uploaded as knowledge to a Custom GPT are retained indefinitely, while files used for other purposes (e.g., Advanced Data Analysis) are retained for a duration that varies based on the user's plan[3].

In summary, OpenAI Custom GPTs support a wide range of file types, including text files, spreadsheets, presentations, documents, and images, which can be used to extend the GPT's knowledge and capabilities for specific use cases.

Quellen [1] OpenAI Custom GPTs: What You Need to Worry About https://www.paloaltonetworks.com/blog/prisma-cloud/openai-custom-gpts-security/ [2] OpenAI GPT-3 API: Which file formats can be used for fine-tuning? https://stackoverflow.com/questions/75559672/openai-gpt-3-api-which-file-formats-can-be-used-for-fine-tuning [3] File uploads FAQ - OpenAI Help Center https://help.openai.com/en/articles/8555545-file-uploads-faq [4] Introducing GPTs - OpenAI https://openai.com/blog/introducing-gpts

What are maximum sizes in number of files and file size limits

Based on the search results, the key file size and upload limits for OpenAI Custom GPTs are:

  1. Maximum number of files per GPT: 20 files[3]

  2. Maximum file size per file: 512 MB[2]

  3. Maximum total file size across all files uploaded to a GPT: 100 GB per organization[2]

  4. Maximum token count for text/document files (excluding spreadsheets): 2 million tokens per file[2]

  5. Maximum image file size: 20 MB per image[2]

The search results also indicate that images embedded within documents or presentations are not yet supported[2].

Additionally, the files uploaded as knowledge sources to a Custom GPT are retained indefinitely, while files used for other purposes (e.g., Advanced Data Analysis) are retained for a duration that varies based on the user's plan[2].

So in summary, the key limits are 20 files per GPT, 512 MB per file, and a 100 GB total per organization, with some additional restrictions on token counts and image sizes.

Quellen [1] Number of files you can upload on a GPT - OpenAI Developer Forum https://community.openai.com/t/number-of-files-you-can-upload-on-a-gpt/523616 [2] File uploads FAQ - OpenAI Help Center https://help.openai.com/en/articles/8555545-file-uploads-faq [3] GPTs knowledge capacity limits - OpenAI Developer Forum https://community.openai.com/t/gpts-knowledge-capacity-limits/492955 [4] What is the max amount of data an Azure OpenAI Gpt-4 model can ... https://learn.microsoft.com/en-us/answers/questions/1600250/what-is-the-max-amount-of-data-an-azure-openai-gpt

What is a token and how can it be calculated?

A token represents the smallest meaningful unit of text in the context of large language models like GPT-3 and GPT-4[2][4]. It can be a single character, a group of characters, a word, or even a punctuation mark[3].

To calculate the number of tokens in a given text, you can use a tokenizer tool or follow these general guidelines:

  • In English, 1 token is approximately equal to 4 characters or 0.75 words[2][4]

  • 100 tokens are roughly equivalent to 75 words[2]

  • 1-2 sentences contain around 30 tokens, while 1 paragraph is about 100 tokens[2]

  • 1,500 words are approximately equal to 2,048 tokens[2]

The exact number of tokens can vary depending on the language and the tokenization method used[2][4]. For example, in Spanish and French, 1 word is about 2 tokens[3].

Some key points about tokens:

  • Punctuation marks and special characters count as individual tokens[3]

  • Emojis range from 2 to 3 tokens[3]

  • The tokenization process can split words into sub-word tokens based on context[2]

  • Newer models like GPT-4 use different tokenizers than previous versions, resulting in varying token counts for the same input text[2]

To get an accurate token count for your text, you can use online tools like the GPT-4 Token Counter[3] or the Tokenizer tool provided by OpenAI[2].

Quellen [1] Token Counter https://tokenizer.streamlit.app [2] What are tokens and how to count them? - OpenAI Help Center https://help.openai.com/en/articles/4936856-what-are-tokens-and-how-to-count-them [3] GPT-4 Token Counter Online - Quizgecko https://quizgecko.com/tools/token-counter [4] What Are Tokens and How to Calculate Them - LinkedIn https://www.linkedin.com/pulse/what-tokens-how-calculate-them-rodrigo-andrade

What is a token and how can it be calculated?

A token represents the smallest meaningful unit of text in the context of large language models like GPT-3 and GPT-4[2][4]. It can be a single character, a group of characters, a word, or even a punctuation mark[3].

To calculate the number of tokens in a given text, you can use a tokenizer tool or follow these general guidelines:

  • In English, 1 token is approximately equal to 4 characters or 0.75 words[2][4]

  • 100 tokens are roughly equivalent to 75 words[2]

  • 1-2 sentences contain around 30 tokens, while 1 paragraph is about 100 tokens[2]

  • 1,500 words are approximately equal to 2,048 tokens[2]

The exact number of tokens can vary depending on the language and the tokenization method used[2][4]. For example, in Spanish and French, 1 word is about 2 tokens[3].

Some key points about tokens:

  • Punctuation marks and special characters count as individual tokens[3]

  • Emojis range from 2 to 3 tokens[3]

  • The tokenization process can split words into sub-word tokens based on context[2]

  • Newer models like GPT-4 use different tokenizers than previous versions, resulting in varying token counts for the same input text[2]

To get an accurate token count for your text, you can use online tools like the GPT-4 Token Counter[3] or the Tokenizer tool provided by OpenAI[2].

Quellen

[1] Token Counter https://tokenizer.streamlit.app

[2] What are tokens and how to count them? - OpenAI Help Center https://help.openai.com/en/articles/4936856-what-are-tokens-and-how-to-count-them

[3] GPT-4 Token Counter Online - Quizgecko https://quizgecko.com/tools/token-counter

[4] What Are Tokens and How to Calculate Them - LinkedIn https://www.linkedin.com/pulse/what-tokens-how-calculate-them-rodrigo-andrade I

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Last updated 1 year ago