Prevent `TextGenerationPipeline._sanitize_parameters` from overriding previously provided parameters
Author: yting27
Pull request: yes

# What does this PR do?

Below is the code example I used. The `max_length` and `truncation` (as well as `padding` and `add_special_tokens`) parameters passed to the `pipeline` method are overridden when generating output.
```
from transformers import pipeline


template_inst = "Instruct: {prompt}\nOutput:"
max_length = 25

text_generator = pipeline("text-generation", model="openai-gpt", max_length=max_length, max_new_tokens=30, truncation=True)
results = text_generator(template_inst.format(prompt="The personal life of William Shakespeare is somewhat of a mystery. There are two primary sources that provide historians with an outline of his life. One is his work, and the other is official documentation such as church and court records. However, these provide only brief sketches of specific events in his life and yield little insight into the man himself. When Was Shakespeare Born?"))

print(results)
```

Print out `preprocess_params` variables in `Pipeline.__call__()` method:
![image](https://github.com/huggingface/transformers/assets/33386396/dad267c3-f167-4506-ae88-fd47b2987f43)
```
Kwargs: {}
self._preprocess_params: {'add_special_tokens': False, 'truncation': True, 'padding': False, 'max_length': 25, 'max_new_tokens': 30}
preprocess_params: {'add_special_tokens': False, 'truncation': None, 'padding': False, 'max_length': None}
preprocess_params (after): {'add_special_tokens': False, 'truncation': None, 'padding': False, 'max_length': None, 'max_new_tokens': 30}
```
As shown in the output, after `self._sanitize_parameters()` is called, both `truncation` and `max_length` are set to `None`.

I know we can pass the preprocess parameters when calling `text_generator` method (see code above). However, it just doesn't make sense to me that the previous parameters provided should be overridden. Hence I made the change. Feel free to improve if needed 😃 


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## Who can review?
- pipelines: @Narsil

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Comments:
cc @gante @zucchini-nlp 

I think it makes sense and the changes are consistent with the text2text pipeline, where "truncation" is handled similarly