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IBM watsonx.ai
IBM watsonx.ai
  • Installation
  • Setup
    • IBM watsonx.ai for IBM Cloud
    • IBM watsonx.ai software
    • Configuring the HTTP Client
  • API
    • Base
    • Core
    • Federated Learning
    • Data Connections
      • Working with DataConnection
      • DataConnection Modules
      • IterableDatasets Modules
    • AutoAI
      • Working with AutoAI class and optimizer
      • Working with AutoAI RAG class and rag_optimizer
      • AutoAI RAG Parameter Scheme
      • AutoAI experiment
      • Deployment Modules for AutoAI models
    • Foundation Models
      • Embeddings
      • Models
        • ModelInference
        • TSModelInference
        • Model
        • ModelInference for Deployments
      • Tuning
        • Working with TuneExperiment and PromptTuner
        • Working with TuneExperiment and FineTuner
        • Working with TuneExperiment and ILabTuner (BETA)
        • Tuned Model Inference
        • Tune Experiment
        • InstructLab Experiment (BETA)
      • Prompt Template Manager
      • Extensions
        • LangChain
        • LlamaIndex
        • RAG
      • Helpers
      • Custom models
      • Text Detection
      • Text Extractions
      • Parameter Scheme
      • Rerank
      • Deploy on Demand
      • Rate Limits
      • Toolkit
      • VectorIndexes
    • Model Gateway (BETA)
    • Saving external models
  • Samples
  • Migration from ibm_watson_machine_learning
  • V1 Migration Guide
  • Changelog
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SamplesΒΆ

To view sample notebooks for IBM watsonx.ai, refer to Python sample notebooks.

Most of the watsonx.ai notebooks are also available on the Resource hub.

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Migration from ibm_watson_machine_learning
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Saving external models
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