from_pretrained does not load the modified part of model 
## Environment info
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- `transformers` version:
- Platform: Linux
- Python version: 3.7
- PyTorch version (GPU?): 1.7
- Tensorflow version (GPU?): - 
- Using GPU in script?: no 
- Using distributed or parallel set-up in script?: no 

### Who can help
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 Model Cards: @julien-c
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 Model Cards: @julien-c
## Information

Hi
1) I am observing that if one modifies a model lest say T5ForConditionalGeneration and then use  T5ForConditionalGeneration.from_pretrained(...) then not all components of the models are loaded, meaning that the 
parts of the model the user has modified are initialized to random! 

2) I observe this from accuracy, could you tell me how I can check which weights from_pretrained is loading, I am a bit lost in the repository. thanks
## Expected behavior

If the model has been changed to have more layers, .... all the trained weights need to be loaded. 
In the documentation, this is written how from_pretrained works for untouched models, but I cannot see how this works when one modifies the model. <|||||>Hey @juliahane,

could you please provide a code snippet showcasing the unintended behavior? Thanks!<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

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