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IBM Generative AI Python SDK (Tech Preview)
IBM Generative AI Python SDK (Tech Preview)
  • Getting Started
  • V2 Migration Guide
  • Examples
    • Text
      • Stream answer from a model
      • Tokenize text data
      • Chat with a model
      • Compare a set of hyperparameters
      • Get embedding vectors for text data
      • Moderate text data
      • Simple text generation
      • Complex text generation example with a progress bar
    • Models
      • Show information about supported models
    • Tunes
      • Tune a custom model (Prompt Tuning)
    • Prompts
      • Create a custom prompt with variables
    • System Prompts
      • Working with system prompts
    • Files
      • Working with files
    • Users
      • Show information about current user
    • Requests
      • Working with your requests
    • Extra
      • Overriding built-in services
      • Text generation with custom concurrency limit and multiple processes
      • Retrieve metadata for given service method
      • Shutdown Handling
      • Customize underlying API (httpx) Client
      • Enable/Disable logging for SDK
      • Error Handling
      • Vector Databases
        • Chroma DB
          • Create ChromaDB Embedding Function
    • Extensions
      • LocalServer
        • Customize behavior of local client
        • Use a local server with a custom model
      • LangChain
        • Use LangChain generation with a custom template.
        • LangChain Embeddings
        • LangChain SQL Agent
        • Chat with a model using LangChain
        • LangChain agent
        • Text generation using LangChain
        • Serialize LangChain model to a file
        • Streaming response from LangChain
        • QA using native LangChain features
      • LLamaIndex
        • Use a model through LLamaIndex
        • LlamaIndex Embeddings
      • Transformers (HuggingFace)
        • Run Transformers Agents
  • FAQ
  • Changelog

Versions

  • main (unreleased)
  • v3.0.0
  • v2.3.0
  • v2.2.0
  • v2.1.1
  • v2.1.0
  • v2.0.0
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TextΒΆ

The following module contains examples of Text Generation, Tokenization, Moderation, Embeddings and more.

  • Stream answer from a model
  • Tokenize text data
  • Chat with a model
  • Compare a set of hyperparameters
  • Get embedding vectors for text data
  • Moderate text data
  • Simple text generation
  • Complex text generation example with a progress bar
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Stream answer from a model
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