AutoTokenizer/Processor does not work with Mistral3 models
Author: mgoin
Pull request: no
Labels: name: bug

### System Info

Built transformers from source with latest main
```
transformers==4.51.0.dev0 (from file:///home/mgoin/code/transformers)
```

### Who can help?

@Cyrilvallez 

### Information

- [ ] The official example scripts
- [ ] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

```
>>> from transformers import AutoTokenizer, AutoProcessor

>>> tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-Small-3.1-24B-Instruct-2503")
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/mgoin/code/transformers/src/transformers/models/auto/tokenization_auto.py", line 989, in from_pretrained
    tokenizer_class_py, tokenizer_class_fast = TOKENIZER_MAPPING[type(config)]
                                               ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^
  File "/home/mgoin/code/transformers/src/transformers/models/auto/auto_factory.py", line 780, in __getitem__
    raise KeyError(key)
KeyError: <class 'transformers.models.mistral3.configuration_mistral3.Mistral3Config'>

>>> tokenizer = AutoProcessor.from_pretrained("mistralai/Mistral-Small-3.1-24B-Instruct-2503")
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/mgoin/code/transformers/src/transformers/models/auto/processing_auto.py", line 346, in from_pretrained
    return processor_class.from_pretrained(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/mgoin/code/transformers/src/transformers/processing_utils.py", line 1070, in from_pretrained
    args = cls._get_arguments_from_pretrained(pretrained_model_name_or_path, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/mgoin/code/transformers/src/transformers/processing_utils.py", line 1134, in _get_arguments_from_pretrained
    args.append(attribute_class.from_pretrained(pretrained_model_name_or_path, **kwargs))
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/mgoin/code/transformers/src/transformers/models/auto/tokenization_auto.py", line 989, in from_pretrained
    tokenizer_class_py, tokenizer_class_fast = TOKENIZER_MAPPING[type(config)]
                                               ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^
  File "/home/mgoin/code/transformers/src/transformers/models/auto/auto_factory.py", line 780, in __getitem__
    raise KeyError(key)
KeyError: <class 'transformers.models.mistral3.configuration_mistral3.Mistral3Config'>
```

### Expected behavior

Based on the model documentation here https://huggingface.co/docs/transformers/v4.50.0/en/model_doc/mistral3#inference-on-a-single-image
I would expect `AutoProcessor.from_pretrained` to work.

Comments:
Was this resolved? I am getting this issue using Mistral Small 3.1 and Mistral Small 3.2 using the latest release of transformers.

Edit: Figured it out, The model I was loading was still in the Mistral Format and needed to be converted to the HF format.

This PR should fix it: https://github.com/huggingface/transformers/pull/42198