Conditional generation with T5
## Environment info
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     Don't forget to fill out the missing fields in that output! -->

- `transformers` version: 4.3.2
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch version (GPU?): 1.7.0+cu101 (True)
- Tensorflow version (GPU?): 2.4.1 (True)
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: no

### Who can help
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Models:

- t5: @patrickvonplaten, @patil-suraj

Library:

- text generation: @patrickvonplaten
- tokenizers: @n1t0, @LysandreJik

 -->

## Information

Model I am using (Bert, XLNet ...): T5

The problem arises when using:
* [ ] the official example scripts: (give details below)
* Generating conditional text from T5
```
from transformers import T5Tokenizer, T5ForConditionalGeneration
tokenizer = T5Tokenizer.from_pretrained('t5-3b')
model = T5ForConditionalGeneration.from_pretrained('t5-3b')
input_ids = tokenizer('The <extra_id_0> walks in <extra_id_1> park', return_tensors='pt').input_ids
labels = tokenizer('<extra_id_0> cute dog <extra_id_1> the <extra_id_2> </s>', return_tensors='pt').input_ids
outputs = model(input_ids=input_ids, labels=labels)
loss = outputs.loss
logits = outputs.logits
input_ids = tokenizer("summarize: studies have shown that owning a dog is good for you ", return_tensors="pt").input_ids  # Batch size 1
outputs = model.generate(input_ids)
```

## To reproduce

Steps to reproduce the behavior:

1. Run the code above

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## Expected behavior

<!-- A clear and concise description of what you would expect to happen. -->
To see the generated text. Rather, the model outputs a torch Tensor like so
`tensor([[   0,  363,   19,    8, 1784,   13, 1473,   58,    1]])`
How do I get words out of it rather than a tensor?
You can decode them back to a string using `T5Tokenizer`, like so:

`tokenizer.decode(outputs.squeeze().tolist(), skip_special_tokens=True)`

Btw, for a really good guide on the different generation strategies of models like T5, see this blog post: https://huggingface.co/blog/how-to-generate<|||||>This post was really helpful, thanks!