src

docs/api_reference.md

@@ -0,0 +1,12 @@
+# API Reference
+
+## TabPFNClassifier
+
+::: tabpfn.scripts.transformer_prediction_interface.TabPFNClassifier
+    handler: python
+    options:
+      members:
+        - __init__
+        - fit
+        - predict
+        - predict_proba

docs/index.md

@@ -11,10 +11,9 @@ TabPFN is a cutting-edge neural network designed specifically for tabular data p
 
 ## Quick Links
 
-- [Installation](docs/installation.md): Get started by installing TabPFN in your environment.
-- [Getting Started](docs/getting_started.md): Learn how to quickly train and evaluate your first TabPFN model.
-- [Classification](docs/classification.md): Dive into using TabPFN for classification tasks, with examples and tips.
-- [Regression](docs/regression.md): Explore how to apply TabPFN to regression problems, including setup and evaluation.
+- [Getting Started](getting_started.md): Learn how to quickly train and evaluate your first TabPFN model.
+- [Classification](classification.md): Dive into using TabPFN for classification tasks, with examples and tips.
+- [Regression](regression.md): Explore how to apply TabPFN to regression problems, including setup and evaluation.
 
 ## Getting Help
 

mkdocs.yml

@@ -6,6 +6,35 @@ theme:
 repo_url: https://github.com/automl/TabPFN
 plugins:
   - search
+  - mkdocstrings:
+      default_handler: python
+      handlers:
+        python:
+          paths: [src]
+          rendering:
+            show_source: true
+          options:
+            docstring_section_style: list
+            filters: ["!^_"]
+            heading_level: 1
+            inherited_members: true
+            merge_init_into_class: true
+            separate_signature: true
+            show_root_heading: true
+            show_root_full_path: false
+            show_signature_annotations: true
+            show_symbol_type_heading: true
+            show_symbol_type_toc: true
+            signature_crossrefs: true
+            summary: true
+
+nav:
+  - Home: index.md
+  - Getting Started: getting_started.md
+  - Classification: classification.md
+  - Regression: regression.md
+  - API Reference: api_reference.md
+
 #extra:
 #  analytics:
 #    provider: google