text: 
  
  TITLE
  BertForSequenceClassification  -> TFBertForSequenceClassification causes 'bert.embeddings.position_ids' not used error
  
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  ## Environment info
  <!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
       Don't forget to fill out the missing fields in that output! -->
       
  - `transformers` version: 3.3.1
  - Platform: Linux-4.9.0-13-amd64-x86_64-with-debian-9.13
  - Python version: 3.7.8
  - PyTorch version (GPU?): 1.4.0 (True)
  - Tensorflow version (GPU?): 2.3.1 (True)
  - Using GPU in script?: No
  - Using distributed or parallel set-up in script?: No
  
  ### Who can help
  <!-- Your issue will be replied to more quickly if you can figure out the right person to tag with @
   If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
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   albert, bert, GPT2, XLM: @LysandreJik 
  
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  ## Information
  
  Model I am using (Bert, XLNet ...):
  
  ```
  from transformers import BertTokenizer, TFBertModel, TFBertForSequenceClassification,BertForSequenceClassification
  import tensorflow as tf
  
  tokenizer = BertTokenizer.from_pretrained('bert-base-cased')
  model = TFBertForSequenceClassification.from_pretrained('output', from_pt=True)
  
  ```
  
  I'm loading TFBertForSequenceClassification from a BertForSequenceClassification pytorch SavedModel and get this error: 
  
  `Some weights of the PyTorch model were not used when initializing the TF 2.0 model TFBertForSequenceClassification: ['bert.embeddings.position_ids']`
  
  I've done this before with this exact model and not had these issues. 
  