Update README.md

README.md

@@ -59,8 +59,8 @@ Sample usage:
 ```python
 from transformers import AutoModel, AutoTokenizer
 
-tokenizer = AutoTokenizer.from_pretrained('dicta-il/dictabert-parse')
-model = AutoModel.from_pretrained('dicta-il/dictabert-parse', trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained('dicta-il/dictabert-large-parse')
+model = AutoModel.from_pretrained('dicta-il/dictabert-large-parse', trust_remote_code=True)
 
 model.eval()
 
@@ -492,6 +492,14 @@ Output:
     ],
     "root_idx": 2,
     "ner_entities": [
+      {
+        "phrase": "1948",
+        "label": "TIMEX",
+        "start": 5,
+        "end": 9,
+        "token_start": 1,
+        "token_end": 1
+      },
       {
         "phrase": "אפרים קישון",
         "label": "PER",
@@ -553,7 +561,7 @@ Results:
 
 ## Citation
 
-If you use DictaBERT-parse in your research, please cite ```MRL Parsing without Tears: The Case of Hebrew```
+If you use DictaBERT-large-parse in your research, please cite ```MRL Parsing without Tears: The Case of Hebrew```
 
 **BibTeX:**