Update README.md

README.md

@@ -5,9 +5,9 @@ license: mit
 ```python
 import pandas as pd
 from datasets import load_dataset
-from transformers import MBartForConditionalGeneration
-model = MBartForConditionalGeneration.from_pretrained("vaishali/BnTQA-M2M")
-tokenizer = AutoTokenizer.from_pretrained(args.pretrained_model_name, src_lang="bn", tgt_lang="bn")
+from transformers import M2M100ForConditionalGeneration
+model = M2M100ForConditionalGeneration.from_pretrained("vaishali/BnTQA-M2M")
+tokenizer = AutoTokenizer.from_pretrained("vaishali/BnTQA-M2M", src_lang="bn", tgt_lang="bn")
 forced_bos_id = forced_bos_token_id = tokenizer.get_lang_id("bn")
 
 
@@ -21,7 +21,7 @@ def process_row(row: List, row_index: int):
   row_cell_values = []
   for cell_value in row:
       if isinstance(cell_value, int) or isinstance(cell_value, float):
-          cell_value = self.convert_engDigit_to_bengali(str(cell_value))
+          cell_value = convert_engDigit_to_bengali(str(cell_value))
           row_cell_values.append(str(cell_value))
       else:
           row_cell_values.append(cell_value)
@@ -34,7 +34,7 @@ def process_row(row: List, row_index: int):
 def process_table(table_content: Dict):
   table_str = process_header(table_content["header"]) + " "
   for i, row_example in enumerate(table_content["rows"]):
-      table_str += self.process_row(row_example, row_index=i + 1) + " "
+      table_str += process_row(row_example, row_index=i + 1) + " "
   return table_str.strip()
 
 # load the dataset