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Getting Started
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Tutorials
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Code Reference
- Tabpfn
  Tabpfn
  - Base
  - Classifier
  - Constants
  - Inference
  - Preprocessing
  - Regressor
  - Utils
  - Model
    Model
    
    Bar distribution
    
    Config
    
    Encoders
    
    Layer
    
    Loading
    
    Memory
    
    Mlp
    
    Multi head attention
    
    Preprocessing
    
    Transformer
- Tabpfn client
  Tabpfn client
  - Browser auth
  - Client
  - Config
  - Constants
  - Estimator
  - Prompt agent
  - Service wrapper
  - Tabpfn common utils
    Tabpfn common utils
    
    Regression pred result
    
    Utils
- Tabpfn extensions
  Tabpfn extensions
  - Utils
  - Utils todo
  - Benchmarking
    Benchmarking
    
    Experiment
  - Classifier as regressor
    Classifier as regressor
    
    Classifier as regressor
  - Hpo
    Hpo
    
    Search space
    
    Tuned tabpfn
  - Interpretability
    Interpretability
    
    Experiments
    
    Feature selection
    
    Shap
  - Many class
    Many class
    
    Many class classifier
  - Post hoc ensembles
    Post hoc ensembles
    
    Abstract validation utils
    
    Greedy weighted ensemble
    
    Pfn phe
    
    Save splitting
    
    Sklearn interface
  - Rf pfn
    Rf pfn
    
    SklearnBasedDecisionTreeTabPFN
    
    SklearnBasedRandomForestTabPFN
    
    Configs
    
    Utils
  - Scoring
    Scoring
    
    Scoring utils
  - Sklearn ensembles
    Sklearn ensembles
    
    Configs
    
    Meta models
    
    Weighted ensemble
  - Unsupervised
    Unsupervised
    
    Experiments
    
    Unsupervised

configs ¶