Update README.md

README.md

@@ -6,8 +6,11 @@ language:
 pipeline_tag: token-classification
 ---
 Named entity recognition On Persian dataset
+
 traindataset=20484 persian sentense 
+
 valdataset=2561
+
 AutoTokenizer=HooshvareLab/bert-fa-base-uncased
 
 ner_tags=
@@ -26,10 +29,15 @@ ner_tags=
 
 training_args=
     learning_rate=2e-5,
+    
     per_device_train_batch_size=16,
+    
     per_device_eval_batch_size=16,
+    
     num_train_epochs=4,
+    
     weight_decay=0.01
+    
 
 Training Loss=0.001000
 
@@ -43,4 +51,19 @@ sample2:
   'entity': 'B-pers',
   'score': 0.99988234,
   'index': 2,
-  'word': 'عباس',
+  'word': 'عباس',
+
+
+for use this model:
+
+    from transformers import pipeline
+    
+    pipe = pipeline("token-classification", model="NLPclass/Named_entity_recognition_persian")
+
+    sentence = ""
+
+    predicted_ner = pipe(sentence)
+    
+    for entity in predicted_ner:
+    
+        print(f"Entity: {entity['word']}, Label: {entity['entity']}")