[Feature Request] Add timestamp prediction for TF Whisper
### System Info

Latest Version.
On google Colab

### Who can help?

@sanchit-gandhi @connor-henderson 

### Information


I am trying to convert tensorflow whisper to tflite but turns out that TFWhisper doesnt want to output timestamp tokens.

- [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

```
import tensorflow as tf


# Importing necessary classes from transformers 
from transformers import WhisperProcessor, WhisperFeatureExtractor, TFWhisperForConditionalGeneration, WhisperTokenizer

# Importing necessary functions from datasets
from datasets import load_dataset

# Creating an instance of AutoProcessor from the pretrained model
feature_extractor = WhisperFeatureExtractor.from_pretrained("openai/whisper-tiny.en")
tokenizer = WhisperTokenizer.from_pretrained("openai/whisper-tiny.en", predict_timestamps=True)
processor = WhisperProcessor(feature_extractor, tokenizer)

# Creating an instance of TFWhisperForConditionalGeneration from the pretrained model
model = TFWhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny.en")

# Loading dataset
ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")

# Inputs
inputs = processor(ds[0]["audio"]["array"], return_tensors="tf")
input_features = inputs.input_features

# Generating Transcription
generated_ids = model.generate(input_features=input_features, return_timestamps=True)
transcription = processor.tokenizer.decode(generated_ids[0], decode_with_timestamps=True)
print(transcription)
```
<|startoftranscript|><|notimestamps|> Mr. Quilter is the apostle of the middle classes, and we are glad to welcome his gospel.<|endoftext|>


### Expected behavior




While the same tokenizer with ```predict_timestamps=True``` works as expected in pytorch:
```
import torch
from transformers import WhisperForConditionalGeneration

model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny.en")

ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")

inputs = processor(ds[0]["audio"]["array"], return_tensors="pt")
input_features = inputs.input_features

generated_ids = model.generate(inputs=input_features, return_timestamps=True)

transcription = processor.tokenizer.decode(generated_ids[0], decode_with_timestamps=True)
transcription
```
<|startoftranscript|><|0.00|> Mr. Quilter is the apostle of the middle classes, and we are glad to welcome his gospel.<|5.44|><|endoftext|>

Will be closed by https://github.com/huggingface/transformers/pull/21334<|||||>@ArthurZucker do you maybe have some time to finish https://github.com/huggingface/transformers/pull/21334? Alternatively we can open this one up to the community if not!<|||||>Yep let's open it to the community I'm a bit short on time 😓 <|||||>If you come across this feature request and are interested in having a go, that's awesome, it's great to see! Feel free to resume the PR @ArthurZucker started at #21334 - it provides the scaffold you need to add this feature!<|||||>Sure, I’ll dig it up and share tomorrow … it is only transcribing for now but with timestamps. <|||||>@nyadla-sys https://colab.research.google.com/drive/1qXcgILcA-HPEYqAYPrxQQ1TRwXerErDk?usp=sharing<|||||>Hey @nyadla-sys - cool to see that you're using the TF model for inference! Could I respectfully ask that we try and keep the GitHub issue thread relevant to the issue being discussed? For other TF / TFLite issues, you can either open a new issue or open a post on the forum: https://discuss.huggingface.co

Thanks!<|||||>> Hey @nyadla-sys - cool to see that you're using the TF model for inference! Could I respectfully ask that we try and keep the GitHub issue thread relevant to the issue being discussed? For other TF / TFLite issues, you can either open a new issue or open a post on the forum: https://discuss.huggingface.co
> 
> Thanks!

removed my comments ,sorry to spam<|||||>May I please try to tackle this with @0525hhgus on the weekends?
Thank you and I hope you all have a great weekend!<|||||>Of course! Feel free to continue @ArthurZucker's PR https://github.com/huggingface/transformers/pull/21334 - it's already in a good state regarding TF Whisper timestamps. You just need to do the TF Whisper part, the Flax part has been merged already :)

Alternatively you can open a new PR and copy across the relevant code changes if you're more comfortable doing that. Feel free to tag myself and Arthur in any PR you work on - we're on hand to help with questions / queries!