Add enable_list_inference and intermediate_format as new BQ configurations for 1.7

website/docs/reference/resource-configs/bigquery-configs.md

@@ -902,3 +902,24 @@ As with most data platforms, there are limitations associated with materialized
 Find more information about materialized view limitations in Google's BigQuery [docs](https://cloud.google.com/bigquery/docs/materialized-views-intro#limitations).
 
 </VersionBlock>
+
+<VersionBlock firstVersion="1.9">
+
+## Python models
+
+The BigQuery adapter supports Python models with the following additional configuration parameters:
+
+| Parameter               | Type        | Required | Default   | Valid values     |
+|-------------------------|-------------|----------|-----------|------------------|
+| `enable_list_inference` | `<boolean>` | no       | `True`    | `True`, `False`  |
+| `intermediate_format`   | `<string>`  | no       | `parquet` | `parquet`, `orc` |
+
+### The `enable_list_inference` parameter
+The `enable_list_inference` parameter enables a PySpark data frame to read multiple records in the same operation.
+By default, this is set to `True` to support the default `intermediate_format` of `parquet`.
+
+### The `intermediate_format` parameter
+The `intermediate_format` parameter specifies which file format to use when writing records to a table. The default is `parquet`.
+This parameter became configurable when the default write method changed from `direct` to `indirect` to support partitioning and clustering.
+
+</VersionBlock>