Repository: huggingface/transformers
Pull request: [ `vllm x v5`] nit

# What does this PR do?
Removed the tokenizer_class attr was never there to begin with, and kwargs are now supported. 
This was failing some test on vllm ci. Fixes https://buildkite.com/vllm/ci/builds/57601/steps/canvas?sid=019d1aec-aa5a-41db-bac6-4f42397279d5 
```python
In [6]: pip = pipeline("text-generation", "XiaomiMiMo/MiMo-7B-Base")
The repository XiaomiMiMo/MiMo-7B-Base contains custom code which must be executed to correctly load the model. You can inspect the repository content at https://hf.co/XiaomiMiMo/MiMo-7B-Base .
 You can inspect the repository content at https://hf.co/XiaomiMiMo/MiMo-7B-Base.
rue`.an avoid this prompt in future by passing the argument `trust_remote_code=T 

Do you wish to run the custom code? [y/N] y
The repository XiaomiMiMo/MiMo-7B-Base contains custom code which must be executed to correctly load the model. You can inspect the repository content at https://hf.co/XiaomiMiMo/MiMo-7B-Base .
 You can inspect the repository content at https://hf.co/XiaomiMiMo/MiMo-7B-Base.
rue`.an avoid this prompt in future by passing the argument `trust_remote_code=T 

Do you wish to run the custom code? [y/N] y
The repository XiaomiMiMo/MiMo-7B-Base contains custom code which must be executed to correctly load the model. You can inspect the repository content at https://hf.co/XiaomiMiMo/MiMo-7B-Base .
 You can inspect the repository content at https://hf.co/XiaomiMiMo/MiMo-7B-Base.
rue`.an avoid this prompt in future by passing the argument `trust_remote_code=T 

Do you wish to run the custom code? [y/N] y
modeling_mimo.py: 3.53kB [00:00, 2.34MB/s]
A new version of the following files was downloaded from https://huggingface.co/XiaomiMiMo/MiMo-7B-Base:
- modeling_mimo.py
. Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.
model.safetensors.index.json: 37.0kB [00:00, 16.4MB/s]
Fetching 4 files: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 4/4 [01:58<00:00, 29.64s/it]
Download complete: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 15.7G/15.7G [01:58<00:00, 132MB/s]
Loading weights: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 451/451 [00:00<00:00, 6320.50it/s]
generation_config.json: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 138/138 [00:00<00:00, 582kB/s]
The repository XiaomiMiMo/MiMo-7B-Base contains custom code which must be executed to correctly load the model. You can inspect the repository content at https://hf.co/XiaomiMiMo/MiMo-7B-Base .
 You can inspect the repository content at https://hf.co/XiaomiMiMo/MiMo-7B-Base.
rue`.an avoid this prompt in future by passing the argument `trust_remote_code=T 

Do you wish to run the custom code? [y/N] y
tokenizer_config.json: 7.23kB [00:00, 6.69MB/s]
vocab.json: 2.78MB [00:00, 11.2MB/s]
merges.txt: 1.67MB [00:00, 12.6MB/s]
tokenizer.json: 7.03MB [00:00, 21.2MB/s]

In [7]: pip("Hey how are you?")
Both `max_new_tokens` (=256) and `max_length`(=20) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
Out[7]: [{'generated_text': "Hey how are you? I'm in the same boat as you. I'm 18 years old and I'm currently a sophomore in college. I've been struggling with depression for about 5 years now and it's getting worse. I've been on medication for a long time to help me cope, but I still struggle. I'm not sure if I'm going to make it through college. I've been thinking about suicide a lot lately. I don't know if I can do it. I don't know if I'm strong enough. I'm just lost. I don't know what to do. I'm sorry for being a burden to you. I hope you can find some relief."}]

```
checked and this works expectedly. 
```python
config = AutoConfig.from_pretrained("XiaomiMiMo/MiMo-7B-Base", trust_remote_code=True)
```



Changed files:
filename: src/transformers/configuration_utils.py
patch: @@ -32,7 +32,6 @@
 from .generation.configuration_utils import GenerationConfig
 from .modeling_gguf_pytorch_utils import load_gguf_checkpoint
 from .modeling_rope_utils import RotaryEmbeddingConfigMixin
-from .tokenization_utils_base import PreTrainedTokenizerBase
 from .utils import (
     CONFIG_NAME,
     PushToHubMixin,
@@ -234,9 +233,6 @@ class PreTrainedConfig(PushToHubMixin, RotaryEmbeddingConfigMixin):
     label2id: dict[str, int] | dict[str, str] | None = None
     problem_type: Literal["regression", "single_label_classification", "multi_label_classification"] | None = None
 
-    # Tokenizer kwargs
-    tokenizer_class: str | PreTrainedTokenizerBase | None = None
-
     def __post_init__(self, **kwargs):
         # BC for the `torch_dtype` argument instead of the simpler `dtype`
         # Do not warn, as it would otherwise always be triggered since most configs on the hub have `torch_dtype`

filename: src/transformers/models/mt5/configuration_mt5.py
patch: @@ -29,8 +29,6 @@ class MT5Config(PreTrainedConfig):
         The maximum distance of the longer sequences for the bucket separation.
     feed_forward_proj (`str`, *optional*, defaults to `"gated-gelu"`):
         Type of feed forward layer to be used. Should be one of `"relu"` or `"gated-gelu"`.
-    tokenizer_class (`str`, *optional*, defaults to `"T5Tokenizer"`):
-        The tokenizer's class name.
     """
 
     model_type = "mt5"
@@ -57,7 +55,6 @@ class MT5Config(PreTrainedConfig):
     feed_forward_proj: str = "gated-gelu"
     is_encoder_decoder: bool = True
     use_cache: bool = True
-    tokenizer_class: str = "T5Tokenizer"
     tie_word_embeddings: bool = True
     bos_token_id: int | None = None
     pad_token_id: int | None = 0

filename: src/transformers/models/umt5/configuration_umt5.py
patch: @@ -29,8 +29,6 @@ class UMT5Config(PreTrainedConfig):
         The maximum distance of the longer sequences for the bucket separation.
     feed_forward_proj (`str`, *optional*, defaults to `"gated-gelu"`):
         Type of feed forward layer to be used. Should be one of `"relu"` or `"gated-gelu"`.
-    tokenizer_class (`str`, *optional*, defaults to `"T5Tokenizer"`):
-        The tokenizer's class name
     """
 
     model_type = "umt5"
@@ -57,7 +55,6 @@ class UMT5Config(PreTrainedConfig):
     feed_forward_proj: str = "gated-gelu"
     is_encoder_decoder: bool = True
     use_cache: bool = True
-    tokenizer_class: str = "T5Tokenizer"
     pad_token_id: int | None = 0
     eos_token_id: int | list[int] | None = 1
     decoder_start_token_id: int | None = 0

filename: tests/utils/test_configuration_utils.py
patch: @@ -146,7 +146,6 @@ def test_config_common_kwargs_is_complete(self):
             [
                 "transformers_version",
                 "is_encoder_decoder",
-                "tokenizer_class",
                 "_name_or_path",
                 "_commit_hash",
                 "_output_attentions",