Update README.md

change instruction to point to 2025-01-10

README.md

@@ -17,15 +17,15 @@ In order to access Foursquare's Open Source Places data, it is recommended to us
 
 - For Spark 3, you can use the `read_parquet` helper function from the [HF Spark documentation](https://huggingface.co/docs/hub/datasets-spark). It provides an easy API to load a Spark Dataframe from Hugging Face, without having to download the full dataset locally:
   ```python
-  places = read_parquet("hf://datasets/foursquare/fsq-os-places/release/dt=*/places/parquet/*.parquet")
+  places = read_parquet("hf://datasets/foursquare/fsq-os-places/release/dt=2025-01-10/places/parquet/*.parquet")
   ```
 - For Spark 4, there will be an official Hugging Face Spark data source available.
 
 Alternatively you can download the following files to your local disk or cluster:
 
 - Parquet Files:
-  - **Places** - [release/dt=2024-12-03/places/parquet](https://huggingface.co/datasets/foursquare/fsq-os-places/tree/main/release/dt%3D2024-12-03/places/parquet)
-  - **Categories** - [release/dt=2024-12-03/categories/parquet](https://huggingface.co/datasets/foursquare/fsq-os-places/tree/main/release/dt%3D2024-12-03/categories/parquet)
+  - **Places** - [release/dt=2025-01-10/places/parquet](https://huggingface.co/datasets/foursquare/fsq-os-places/tree/main/release/dt%3D2025-01-10/places/parquet)
+  - **Categories** - [release/dt=2025-01-10/categories/parquet](https://huggingface.co/datasets/foursquare/fsq-os-places/tree/main/release/dt%3D2025-01-10/categories/parquet)
 
 Hugging Face provides the following [download options](https://huggingface.co/docs/hub/datasets-downloading).