Hi @lewtun
Thanks for your answer
I tried to run old version v3.5.1 by keeping latest version of modeling_deberta.py file with few changes (i needed QuestionAnsweringModelOutput class for SQUAD kind of training)
I was getting below error
    Traceback (most recent call last):
  File "run_squad.py", line 820, in <module>
    main()
  File "run_squad.py", line 734, in main
    model = AutoModelForQuestionAnswering.from_pretrained(
  File "/media/data2/anaconda/envs/transformers-hugginface/lib/python3.8/site-packages/transformers/modeling_auto.py", line 1330, in from_pretrained
    raise ValueError(
ValueError: Unrecognized configuration class <class 'transformers.configuration_deberta.DebertaConfig'> for this kind of AutoModel: AutoModelForQuestionAnswering.
Model type should be one of DistilBertConfig, AlbertConfig, CamembertConfig, BartConfig, LongformerConfig, XLMRobertaConfig, RobertaConfig, SqueezeBertConfig, BertConfig, XLNetConfig, FlaubertConfig, MobileBertConfig, XLMConfig, ElectraConfig, ReformerConfig, FunnelConfig, LxmertConfig. 

find_sublist_indices i created by taking ref of this notebook 4 which uses a fast tokenizer, I am trying to do the same without fast tokenizer
Fast tokenizer has method called char_to_token i am trying to implement the same on Python based tokenizer.
Hi @valhalla,
Can you tell me how can i use the same notebook 4 without fast tokenizer since it was created by you?