update README

README.md

@@ -31,7 +31,7 @@ This competition features two independent synthetic data challenges that you can
 
 For each challenge, generate a dataset with the same size and structure as the original, capturing its statistical patterns — but without being significantly closer to the (released) original samples than to the (unreleased) holdout samples.
 
-Train a generative model that generalizes well, using any open-source tools (Synthetic Data SDK, synthcity, reprosyn, etc.) or your own solution. Submissions must be fully open-source, reproducible, and runnable within 6 hours on a standard machine.
+Train a generative model that generalizes well, using any open-source tools ([Synthetic Data SDK](https://github.com/mostly-ai/mostlyai), [synthcity](https://github.com/vanderschaarlab/synthcity), [reprosyn](https://github.com/alan-turing-institute/reprosyn), etc.) or your own solution. Submissions must be fully open-source, reproducible, and runnable within 6 hours on a standard machine.
 
 ## Timeline
 
@@ -43,7 +43,7 @@ Train a generative model that generalizes well, using any open-source tools (Syn
 
 ## Dataset Description
 
-This dataset consists of two compressed CSV files used in the MOSTLY AI Prize competition:
+This dataset consists of two CSV files used in the MOSTLY AI Prize competition:
 
 ### Flat Data
 - File: `data/flat/train/flat-training.csv` (26MB, MD5 `d5642dd9b13da0dc1fbac6f92f8e4b20`)