

TITLE
Quick tour_ AutoModel Introduction

COMMENTS
0

REACTIONS
+1: 0
-1: 0
laugh: 0
hooray: 0
heart: 0
rocket: 0
eyes: 0

BODY
### System Info

```shell
- `transformers` version: 3.4.0
- Platform: Linux-4.15.0-144-generic-x86_64-with-debian-buster-sid
- Python version: 3.7.7
- PyTorch version (GPU?): 1.6.0 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in script?: <fill in>
```


### Who can help?

_No response_

### Information

- [x] The official example scripts
- [ ] My own modified scripts

### Tasks

- [x] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

from transformers import AutoModelForSequenceClassification
model_name = "nlptown/bert-base-multilingual-uncased-sentiment"
pt_model = AutoModelForSequenceClassification.from_pretrained(model_name,return_dict=True)


pt_outputs = pt_model(**pt_batch)


from torch import nn
pt_predictions = nn.functional.softmax(pt_outputs.logits, dim=-1)
print(pt_predictions)

### Expected behavior

```shell
from transformers import AutoModelForSequenceClassification
model_name = "nlptown/bert-base-multilingual-uncased-sentiment"
pt_model = AutoModelForSequenceClassification.from_pretrained(model_name)


pt_outputs = pt_model(**pt_batch)


from torch import nn
pt_predictions = nn.functional.softmax(pt_outputs.logits, dim=-1)
print(pt_predictions)

I think pt_outputs.logits is wrong, since from_pretrained(model_name) without return_dict=True.
```
