Skip to main content
The default constructors use the latest default model available through your package or the hosted API. To select a specific version, use the options below. Compare model families, variants, and availability on the Models page.

​
Python client

Update your client with pip install --upgrade tabpfn-client. Select TabPFN-3.5-Plus with create_default_for_version("v3.5"):
For Fast (alpha), select "v3.5-fast". For Thinking, select "v3.5" and add thinking_mode=True:
The same options work with TabPFNRegressor. To use an earlier family, pass its version, such as "v3" or "v2.6". To select a particular model, list the available names and pass one as model_path:
For regression, use TabPFNRegressor.list_available_models() to see the corresponding models.

​
OSS package

Update your package with pip install --upgrade tabpfn. Use ModelVersion to select TabPFN-3.5:
Use ModelVersion.V3_5_FAST for Fast (alpha), or an earlier version such as ModelVersion.V3 or ModelVersion.V2_6. Plus and Thinking are available through the hosted API and client; see Models for availability. TabPFN (v1) is only available through the OSS package, via the v1.0.0 release on GitHub.

​
REST API

Set model_path inside tabpfn_config in your POST /tabpfn/fit request. Use "v3.5_default" for TabPFN-3.5-Plus or "v3.5-fast_default" for Fast (alpha). Both selectors work for classification and regression. The following checkpoint paths select earlier model families:
For example, after uploading your training data, select TabPFN-3.5-Plus for regression:
See the REST API quickstart for the complete upload, fit, and predict flow.