[SpeechLLM] Supports text processing when using LLaMa 3.1
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# What does this PR do ?

This PR fixes two type errors that occured when I was trying to train a SpeechLLM model with [Fast Conformer](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_en_fastconformer_ctc_large) and [LLaMa 3.1](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/llama-3_1-8b-nemo).

1. `TypeError: '>' not supported between instances of 'NoneType' and 'int'`
2. `TypeError: AutoTokenizer.text_to_ids() takes 2 positional arguments but 3 were given`

I used the example script [modular_audio_gpt_train.py](examples/multimodal/speech_llm/modular_audio_gpt_train.py) and config [modular_audio_gpt_config_peft.yaml](examples/multimodal/speech_llm/conf/modular_audio_gpt_config_peft.yaml).

I do not know if training will work out with LLaMa 3/3.1 in general, but at least this fixes the text processing.

I tested this with [LLaMa 2](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/llama-2-7b) as well and it works.

**Collection**: multimodal

# Changelog 
- Handles case when `pad_id` is `None` in the tokenizer
- Passes `sample_alpha` only when tokenizer is `SentencePieceTokenizer` (fixes `TypeError`)

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