update example in README

README.md

@@ -38,7 +38,6 @@ wget https://huggingface.co/zouharvi/PWESuite-metric_learner/resolve/main/rnn_me
 
 Then, in Python, you can run [this example script](https://github.com/zouharvi/pwesuite/blob/master/scripts/50-use_metric_learner.py):
 ```python
-
 from models.metric_learning.model import RNNMetricLearner
 from models.metric_learning.preprocessor import preprocess_dataset_foreign
 from main.utils import load_multi_data
@@ -47,13 +46,21 @@ import tqdm
 import math
 
 data = load_multi_data(purpose_key="all")
-data = preprocess_dataset_foreign(data[:10], features="token_ipa")
+data = preprocess_dataset_foreign(
+  [
+    {"token_ort": "Hello", "token_ipa": None},
+    {"token_ort": "what", "token_ipa": None},
+    {"token_ort": "is", "token_ipa": None},
+    {"token_ort": "pwesuite", "token_ipa": None},
+  ],
+  features="token_ort"
+)
 
 model = RNNMetricLearner(
     dimension=300,
     feature_size=data[0][0].shape[1],
 )
-model.load_state_dict(torch.load("computed/models/rnn_metric_learning_token_ipa_all.pt"))
+model.load_state_dict(torch.load("computed/models/rnn_metric_learning_token_ort_all.pt"))
 
 # some cheap paralelization
 BATCH_SIZE = 32