Update README.md

README.md

@@ -39,20 +39,17 @@ This model classifies input tokens into one of five classes:
 To get started using this model for inference, simply set up an NER `pipeline` like below: 
 
 ```python
-
 from transformers import (AutoModelForTokenClassification, 
                           AutoTokenizer, 
                           pipeline,
                           )
 
 model_checkpoint = "jsylee/scibert_scivocab_uncased-finetuned-ner"
-
-model = AutoModelForTokenClassification.from_pretrained(model_checkpoint, 
-                                                        num_labels=5,
+model = AutoModelForTokenClassification.from_pretrained(model_checkpoint, num_labels=5,
                                                         id2label={0: 'O', 1: 'B-DRUG', 2: 'I-DRUG', 3: 'B-AE', 4: 'I-AE'} 
                                                         )                                                        
-
 tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
+
 model_pipeline = pipeline(task="ner", model=model, tokenizer=tokenizer)
 
 print( model_pipeline ("Abortion, miscarriage or uterine hemorrhage associated with misoprostol (Cytotec), a labor-inducing drug."))