KeyError when using non-default models in Huggingface transformers pipeline

I have no problems using the default model in the sentiment analysis pipeline. 

```# Allocate a pipeline for sentiment-analysis
nlp = pipeline('sentiment-analysis')

nlp('I am a black man.')

>>>[{'label': 'NEGATIVE', 'score': 0.5723695158958435}]
```
But, when I try to customise the pipeline a little by adding a specific model. It throws a KeyError. 



```
nlp = pipeline('sentiment-analysis',
               tokenizer = AutoTokenizer.from_pretrained("DeepPavlov/bert-base-cased-conversational"),
               model = AutoModelWithLMHead.from_pretrained("DeepPavlov/bert-base-cased-conversational"))

nlp('I am a black man.')



>>>---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-55-af7e46d6c6c9> in <module>
      3                tokenizer = AutoTokenizer.from_pretrained("DeepPavlov/bert-base-cased-conversational"),
      4             model = AutoModelWithLMHead.from_pretrained("DeepPavlov/bert-base-cased-conversational"))
----> 5 nlp('I am a black man.')
      6 
      7 

~/opt/anaconda3/lib/python3.7/site-packages/transformers/pipelines.py in __call__(self, *args, **kwargs)
    721         outputs = super().__call__(*args, **kwargs)
    722         scores = np.exp(outputs) / np.exp(outputs).sum(-1, keepdims=True)
--> 723         return [{"label": self.model.config.id2label[item.argmax()], "score": item.max().item()} for item in scores]
    724 
    725 

~/opt/anaconda3/lib/python3.7/site-packages/transformers/pipelines.py in <listcomp>(.0)
    721         outputs = super().__call__(*args, **kwargs)
    722         scores = np.exp(outputs) / np.exp(outputs).sum(-1, keepdims=True)
--> 723         return [{"label": self.model.config.id2label[item.argmax()], "score": item.max().item()} for item in scores]
    724 
    725 

KeyError: 58129

```


# 
Question on SO   -->https://stackoverflow.com/questions/62300836/keyerror-when-using-non-default-models-in-huggingface-transformers-pipeline

The "sentiment-analysis" pipeline is only compatible with text classification models, i.e. those that can be loaded without error with `AutoModelForSequenceClassification`