vllm deploy error

# Issue: ValueError in interns1_vit.py when serving intern-s1 model

## Environment
- OS: Ubuntu 22.04
- CUDA: 12.8.1
- Python: 3.11
- PyTorch: 2.8.0
- vLLM: 0.11.0
- Transformers: 4.57.1

## Command
```bash
vllm serve intern-s1 \
--port 8008 \
--host 0.0.0.0 \
--served-model-name intern-s1 \
--trust-remote-code \
--gpu-memory-utilization 0.9 \
--tensor-parallel-size 8
```

## Error
```
File "/usr/local/lib/python3.11/site-packages/vllm/model_executor/models/interns1_vit.py", line 221, in forward
(Worker_TP0 pid=1145) ERROR 10-24 16:40:22 [multiproc_executor.py:671] B_, N_, H_, D_ = q.shape
(Worker_TP0 pid=1145) ERROR 10-24 16:40:22 [multiproc_executor.py:671] ^^^^^^^^^^^^^^
(Worker_TP0 pid=1145) ERROR 10-24 16:40:22 [multiproc_executor.py:671] ValueError: not enough values to unpack (expected 4, got 3)
```

## Description
When trying to serve the intern-s1 model using vLLM, the service fails with a ValueError in the `interns1_vit.py` file. The error occurs at line 221 where the code attempts to unpack 4 values from `q.shape` but only receives 3 values.

This suggests there's a shape mismatch in the tensor dimensions, likely related to the model's vision transformer implementation. The error occurs during the forward pass of the model execution.

## Expected Behavior
The model should load and serve successfully without shape unpacking errors.