So I’m trying to follow an online guide and have used this notebook: Google Colaboratory and here is the csv file I’m using to finetune it: final.csv - Google Drive
However, I get this traceback when executing the training:
Traceback (most recent call last)
<ipython-input-24-523c0d2a27d3> in <module>()
----> 1 main(trn_df, val_df)

10 frames
<ipython-input-18-aa20b6fc78bc> in main(df_trn, df_val)
     61     # Training
     62     if args.do_train:
---> 63         train_dataset = load_and_cache_examples(args, tokenizer, df_trn, df_val, evaluate=False)
     64 
     65         global_step, tr_loss = train(args, train_dataset, model, tokenizer)

<ipython-input-16-67f62bb60333> in load_and_cache_examples(args, tokenizer, df_trn, df_val, evaluate)
      2 
      3 def load_and_cache_examples(args, tokenizer, df_trn, df_val, evaluate=False):
----> 4     return ConversationDataset(tokenizer, args, df_val if evaluate else df_trn)
      5 
      6 

<ipython-input-23-87cf4adc3093> in __init__(self, tokenizer, args, df, block_size)
     29             self.examples = []
     30             for _, row in df.iterrows():
---> 31                 conv = construct_conv(row, tokenizer)
     32                 self.examples.append(conv)
     33 

<ipython-input-23-87cf4adc3093> in construct_conv(row, tokenizer, eos)
      6     print(row.tolist())
      7     print(type((row.tolist())))
----> 8     conv = [tokenizer.encode(x) + [tokenizer.eos_token_id] for x in row.tolist()]
      9     conv.reverse()
     10     return flatten(list(conv))

<ipython-input-23-87cf4adc3093> in <listcomp>(.0)
      6     print(row.tolist())
      7     print(type((row.tolist())))
----> 8     conv = [tokenizer.encode(x) + [tokenizer.eos_token_id] for x in row.tolist()]
      9     conv.reverse()
     10     return flatten(list(conv))

TypeError: TextEncodeInput must be Union[TextInputSequence, Tuple[InputSequence, InputSequence]]

Does anyone know why?