remove em-dashes

README.md

@@ -18,7 +18,7 @@ tags:
 
 TabFM is a zero-shot tabular foundation model from Google Research. It supports
 classification and regression on structured/tabular data with mixed numerical and
-categorical columns, requiring no fine-tuning or hyperparameter search — training
+categorical columns, requiring no fine-tuning or hyperparameter search - training
 examples are passed as context and predictions are made in a single forward pass.
 
 This repository contains the **JAX/Flax** weights stored as Orbax checkpoints. For the
@@ -144,8 +144,8 @@ tasks.
 ## Performance
 
 TabFM was evaluated on [TabArena](https://tabarena.ai) across 51 datasets
-(38 classification, 13 regression). In zero-shot mode — a single forward pass with no
-hyperparameter search — TabFM outperforms heavily-tuned supervised baselines including
+(38 classification, 13 regression). In zero-shot mode - a single forward pass with no
+hyperparameter search - TabFM outperforms heavily-tuned supervised baselines including
 gradient-boosted trees. The `TabFMClassifier.ensemble()` preset (feature crosses,
 SVD features, NNLS blending) yields further improvements.
 
@@ -169,7 +169,7 @@ deploying in high-stakes settings.
 ## License
 
 The model weights in this repository are released under the
-**TabFM Non-Commercial License v1.0** — see [LICENSE](LICENSE). The source code is
+**TabFM Non-Commercial License v1.0** - see [LICENSE](LICENSE). The source code is
 Apache 2.0 licensed via [google-research/tabfm](https://github.com/google-research/tabfm).
 
 ## Version