T5 Summarization
# 🐛 Bug
T5 summarization code in pipelines.py file gives an error.

## Information

Model I am using: T5

Language I am using the model on (English, Chinese ...): English

The problem arises when using:
pipelines.py official documentation example at line 1146
```
# use t5 in tf
summarizer = pipeline("summarization", model="t5-base", tokenizer="t5-base", framework="tf")
summarizer("Sam Shleifer writes the best docstring examples in the whole world.", min_length=5, max_length=20)
```

## To reproduce
In google colab, I did the following:
```
!pip install transformers
from transformers import pipeline

summarizer = pipeline("summarization", model="t5-base", tokenizer="t5-base", framework="tf")

summarizer("Sam Shleifer writes the best docstring examples in the whole world.", min_length=5, max_length=10)
```

And this gets the following error:
```
Your max_length is set to 200, but you input_length is only 18. You might consider decreasing max_length manually, e.g. summarizer('...', max_length=50)
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-23-0fc603a01733> in <module>()
----> 1 summarizer("Sam Shleifer writes the best docstring examples in the whole world.", min_length=5, max_length=10)

3 frames
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/base_layer.py in __call__(self, *args, **kwargs)
    797     else:
    798       raise ValueError(
--> 799           'The first argument to `Layer.call` must always be passed.')
    800 
    801     call_context = base_layer_utils.call_context()

ValueError: The first argument to `Layer.call` must always be passed.
```

     
- `transformers` version: 2.7.0
- Platform: Google Colab
- PyTorch version (GPU?): 1.4.0 GPU enabled
- Tensorflow version (GPU?): 2.2.0-rcl GPU enabled
- Using GPU in script?: 
- Using distributed or parallel set-up in script?: No

Hi @cformosa, 

Thanks for posting this bug. This seems to be related to the new TF 2.2 release. 
Could you instead use TF2.1 for the moment:

```
!pip install transformers
!pip install tensorflow==2.1
from transformers import pipeline

summarizer = pipeline("summarization", model="t5-base", tokenizer="t5-base", framework="tf")

summarizer("Sam Shleifer writes the best docstring examples in the whole world.", min_length=5, max_length=10
```

Please let me know if you still encounter problems.
