Error while loading Mixtral-8x7B-Instruct-v0.1 tokenizer with AutoTokenizer.from_pretrained

It looks like the latest transformers version supported is 4.36, but as seen from [this issue in transformers](https://github.com/huggingface/transformers/issues/31789), we need to be able to use a newer version of transformers to correctly load in the model.

```python
estimator = HuggingFace(
entry_point='sagemaker_train.py',
source_dir=str(Path()),
instance_type=instance_configs[strategy]["instance_type"],
instance_count=instance_configs[strategy]["instance_count"],
role=role,
transformers_version='4.36.0',
pytorch_version='2.1.0',
py_version='py310',
hyperparameters=hyperparameters,
debugger_hook_config=False,
disable_profiler=True,
max_run=24 * 3600, # 24 hours max
keep_alive_period_in_seconds=1800,
environment={
'HF_TOKEN': huggingface_token,
}
)

estimator.fit(
inputs={
'train': f"s3://{s3_config.bucket}/{s3_config.data_prefix}/train.csv",
'validation': f"s3://{s3_config.bucket}/{s3_config.data_prefix}/val.csv",
'test': f"s3://{s3_config.bucket}/{s3_config.data_prefix}/test.csv"
},
wait=False
)
```

```python
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("mistralai/Mixtral-8x7B-Instruct-v0.1")
```

Traceback (most recent call last):
File "", line 1, in
File "/home/ruser/py310/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py", line 825, in from_pretrained
return tokenizer_class.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
File "/home/ruser/py310/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 2048, in from_pretrained
return cls._from_pretrained(
File "/home/ruser/py310/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 2287, in _from_pretrained
tokenizer = cls(*init_inputs, **init_kwargs)
File "/home/ruser/py310/lib/python3.10/site-packages/transformers/models/llama/tokenization_llama_fast.py", line 133, in __init__
super().__init__(
File "/home/ruser/py310/lib/python3.10/site-packages/transformers/tokenization_utils_fast.py", line 111, in __init__
fast_tokenizer = TokenizerFast.from_file(fast_tokenizer_file)
Exception: data did not match any variant of untagged enum PyPreTokenizerTypeWrapper at line 40 column 3

Start by reproducing the failure with AutoTokenizer.from_pretrained for Mixtral under the estimator configuration shown in sagemaker_train.py, comparing transformers 4.36.0 with a newer version. Trace the toolkit's Transformers version constraints and packaging entry points; done means the tokenizer loads without the PyPreTokenizerTypeWrapper error under a supported configuration.

Written by the indexing model from the issue text.