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gpt-next (Language Learning Assistant POC)

Version 0.0.1 (deprecated)

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  • Token: 4k limit for context learning




  • Model
    • Natural language (NLP)
      • GPT4
      • GPT3.5
    • Language recognition
      • Whisper
    • Image generation
      • DALL-E
    • Text to digital
      • Embeddings
    • Code generation
      • CodeX
| /v1/chat/completions      | gpt-4, gpt-4-0314, gpt-4-32k, gpt-4-32k-0314, gpt-3.5-turbo, gpt-3.5-turbo-0301
| /v1/completions           | text-davinci-003, text-davinci-002, text-curie-001, text-babbage-001, text-ada-001, davinci, curie, babbage, ada
| /v1/edits                 | text-davinci-edit-001, code-davinci-edit-001
| /v1/audio/transcriptions  | whisper-1
| /v1/audio/translations    | whisper-1
| /v1/fine-tunes            | davinci, curie, babbage, ada
| /v1/embeddings            | text-embedding-ada-002, text-search-ada-doc-001
| /v1/moderations           | text-moderation-stable, text-moderation-latest



Completions:
{
 "model": "text-davinci-003",
 "prompt": "Say this is a test",
 "max_tokens": 7, // return content token limit
 "temperature": 0, // higher -> increase the random [Range 0-2]
 "stream": false // server event
}
Chat:
{
 "model": "gpt-3.5-turbo",
 "messages": [
  {
   "role": "system",
   "content": "You are a helpful assistant."
  },
  {
   "role": "user",
   "content": "Who won the NBA title in 2023?"
  },
  {
   "role": "assistant",
   "content": "The Los Angeles Lakers won the World Champion in 2023."
  },
  {
   "role": "user",
   "content": "Where was it played?"
  }
 ], // previous conversation records
 "max_tokens": 7, // return content token limit
 "temperature": 0, // higher -> increase the random [Range 0-2]
 "stream": false // server event
}



  • Prompts:
    • RIO (Role + Input + Output)
      • Role: Assistant / Teacher / Mentor
      • Input
        • Context
        • Task
      • Output
        • Format
        • Style
        • Quantity
        • Way of Thinking



  • Common Prompts:
    • Zero-shot:
      • e.g., how to use javascript slice
    • Few-shot:
      • e.g., provide DSL model (storybook), and build a new webpage
    • Fine-tune:
      • e.g., mix with 10-100GB data, weighted the original model
    • Chain of thought:
      • e.g., solve the problem, step by step



  • Cheatsheet
| blah blah blah: |
| ***             |
| paragraph       |
| ***             |



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