Update README.md

README.md

@@ -41,7 +41,7 @@ configs:
 dataset_info:
 - config_name: train_test
   features:
-  - name: new SMILES
+  - name: SMILES
     dtype: string
   - name: ID
     dtype: int64
@@ -110,11 +110,11 @@ and inspecting the loaded dataset
     >>> train_test
     DatasetDict({
     train: Dataset({
-        features: ['new SMILES', 'ID', 'endpoint', 'MW'],
+        features: ['SMILES', 'ID', 'endpoint', 'MW'],
         num_rows: 6862
     })
     test: Dataset({
-        features: ['new SMILES', 'ID', 'endpoint', 'MW'],
+        features: ['SMILES', 'ID', 'endpoint', 'MW'],
         num_rows: 1714
     })
     })
@@ -141,13 +141,13 @@ then load, featurize, split, fit, and evaluate the a catboost model
     
     split_featurised_dataset = featurise_dataset(
       split_dataset,
-      column = "new SMILES",
+      column = "SMILES",
       representations = load_representations_from_dicts([{"name": "morgan"}, {"name": "maccs_rdkit"}]))
 
     model = load_model_from_dict({
         "name": "cat_boost_classifier",
         "config": {
-            "x_features": ['new SMILES::morgan', 'new SMILES::maccs_rdkit'],
+            "x_features": ['SMILES::morgan', 'SMILES::maccs_rdkit'],
             "y_features": ['endpoint']}})
     
     model.train(split_featurised_dataset["train"])