InternVL 3.5 30B A3B load processor bug
Author: yilian49
Pull request: no
Labels: name: bug

### System Info

- `transformers` version: 4.56.0.dev0
- Platform: Linux-5.15.0-151-generic-x86_64-with-glibc2.35
- Python version: 3.12.11
- Huggingface_hub version: 0.34.4
- Safetensors version: 0.6.2
- Accelerate version: 1.10.1
- Accelerate config:    not found
- DeepSpeed version: not installed
- PyTorch version (accelerator?): 2.8.0+cu126 (CUDA)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using distributed or parallel set-up in script?: <fill in>
- Using GPU in script?: <fill in>
- GPU type: NVIDIA H100 80GB HBM3

### Who can help?

_No response_

### 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

Run 
```
processor = AutoProcessor.from_pretrained(
            "OpenGVLab/InternVL3_5-30B-A3B",
            trust_remote_code=True,   # allow custom code if the repo provides it
            use_fast=True,
        )
```

Raises error
```
Traceback (most recent call last):
  File "/sgl-workspace/test_hf.py", line 22, in <module>
    test_autoprocessor()
  File "/sgl-workspace/test_hf.py", line 6, in test_autoprocessor
    processor = AutoProcessor.from_pretrained(
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/sgl-workspace/transformers/src/transformers/models/auto/processing_auto.py", line 391, in from_pretrained
    return processor_class.from_pretrained(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/sgl-workspace/transformers/src/transformers/processing_utils.py", line 1304, in from_pretrained
    return cls.from_args_and_dict(args, processor_dict, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/sgl-workspace/transformers/src/transformers/processing_utils.py", line 1105, in from_args_and_dict
    processor = cls(*args, **valid_kwargs)
                ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/sgl-workspace/transformers/src/transformers/models/internvl/processing_internvl.py", line 81, in __init__
    self.start_image_token = tokenizer.start_image_token
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/sgl-workspace/transformers/src/transformers/tokenization_utils_base.py", line 1099, in __getattr__
    raise AttributeError(f"{self.__class__.__name__} has no attribute {key}")
AttributeError: Qwen2TokenizerFast has no attribute start_image_token
```

### Expected behavior

Expect the internvl processor to load up properly

Comments:
Hey @yilian49 , the model is hosted on the hub as remote code and we cannot guarantee that it is compatible with recent releases of transformers. Usually authors specify which version to install, and in internVL3.5 docs it states: 

> Please use transformers>=4.52.1 to ensure the model works normally. For the 20B version of our model, transformers>=4.55.0 is required.



This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.

@yilian49 Try to use model with `-HF` suffix. According to [OpenGVLab/InternVL][1] repo, each model has two vairants on HF HUB: incompatible with `transformers` trunk and compatible with it (suffixed with `-HF`).

[1]: https://github.com/OpenGVLab/InternVL

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.