Update README.md

README.md

@@ -2,6 +2,7 @@
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 ---
 
+# Model Card for Model ID
 
 This is a model for word-based spell correction tasks. This model is generated by fine-tuning bart base model.
 
@@ -9,12 +10,12 @@ This model works best for word-based spell correction(not so good with the seque
 
 
 
-
-
-
+## How to Get Started with the Model
+```python
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 tokenizer = AutoTokenizer.from_pretrained("veghar/spell_correct_bart_base")
 model = AutoModelForSeq2SeqLM.from_pretrained("veghar/spell_correct_bart_base")
+
 text='believ'
 text_tok=tokenizer(text,padding=True, return_tensors='tf')
 input_ids = text_tok['input_ids']
@@ -24,5 +25,7 @@ corrected_sentences = tokenizer.batch_decode(outputs, skip_special_tokens=True)
 print('Misspelled word:', text)
 print('Corrected word:', corrected_sentences)
 
->Misspelled word: believ
->Corrected word: ['believe', 'belief', 'believer']
+
+>>Misspelled word: believ
+>>Corrected word: ['believe', 'belief', 'believer']
+```