Conversational pipeline: pop instead of get to avoir duplicate kwargs
The following two tests fail:
```
FAILED tests/test_pipelines_conversational.py::ConversationalPipelineTests::test_integration_torch_conversation
FAILED tests/test_pipelines_conversational.py::ConversationalPipelineTests::test_integration_torch_conversation_encoder_decoder
```

For the following reason:

```
    def _forward(self, model_inputs, minimum_tokens=10, **generate_kwargs):
        max_length = generate_kwargs.get("max_length", self.model.config.max_length)
    
        n = model_inputs["input_ids"].shape[1]
        if max_length - minimum_tokens < n:
            logger.warning(f"Conversation input is to long ({n}), trimming it to ({max_length} - {minimum_tokens})")
            trim = max_length - minimum_tokens
            model_inputs["input_ids"] = model_inputs["input_ids"][:, -trim:]
            if "attention_mask" in model_inputs:
                model_inputs["attention_mask"] = model_inputs["attention_mask"][:, -trim:]
        conversation = model_inputs.pop("conversation")
        model_inputs["max_length"] = max_length
>       output_ids = self.model.generate(**model_inputs, **generate_kwargs)
E       TypeError: generate() got multiple values for keyword argument 'max_length'
```

This PR fixes that.
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.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.<|||||>This was already fixed (by changing removing the assignment statement (making the fix a bit cleaner).

Can't find the associated PR atm tho (was done approx at the same time)