Update README.md

README.md

@@ -9,6 +9,7 @@ pipeline_tag: token-classification
 tags:
 - medical
 - biomedical
+- medkit-lib
 ---
 
 
@@ -53,13 +54,13 @@ Please check the [documentation](https://medkit.readthedocs.io/en/latest/user_gu
 from medkit.core.text import TextDocument
 from medkit.text.ner.hf_entity_matcher import HFEntityMatcher
 
-matcher = HFEntityMatcher(model="dcariasvi/DrBERT-CASM2")
+matcher = HFEntityMatcher(model="camila-ud/DrBERT-CASM2")
 test_doc = TextDocument("Elle souffre d'asthme mais n'a pas besoin d'Allegra")
 
 # detect entities in the raw segment
 detected_entities = matcher.run([test_doc.raw_segment]) 
 msg = "|".join(f"'{entity.label}':{entity.text}" for entity in detected_entities)
-print(f"Text: '{test_doc.text}'\n{msg}")w
+print(f"Text: '{test_doc.text}'\n{msg}")
 ```
 ```
 Text: "Elle souffre d'asthme mais n'a pas besoin d'Allegra"
@@ -108,7 +109,7 @@ Overall|0.7188|0.7660|0.7416
 from medkit.text.metrics.ner import SeqEvalEvaluator
 
 # load the matcher and get predicted entities by document
-matcher = HFEntityMatcher(model="dcariasvi/DrBERT-CASM2")
+matcher = HFEntityMatcher(model="camila-ud/DrBERT-CASM2")
 predicted_entities = [matchers.run([doc.raw_segment]) for doc in test_documents]
 
 # define seqeval evaluator
@@ -128,4 +129,4 @@ evaluator.compute(test_documents,predicted_entities=predicted_entities)
 ```
 ```
 HeKA Research Team, “medkit, a Python library for a learning health system.” https://pypi.org/project/medkit-lib/ (accessed Jul. 24, 2023).
-```
+```