BugFix: AttributeError: 'InternVLChatConfig' object has no attribute 'llm_config'

When loading InternVideo2_5_Chat_8B model or InternVL2_5 series models:
It raises AttributeError: 'InternVLChatConfig' object has no attribute 'llm_config'
Please refer: https://huggingface.co/OpenGVLab/InternVideo2_5_Chat_8B/discussions/14

### Simple Solution for InternVL Configuration Issue
*(Tested with transformers v4.52.4)*

#### Required Modifications
1. **Add Initialization** (configuration_internvl_chat.py:49)
```python
self.vision_config = InternVisionConfig(**vision_config)
self.llm_config = None # Initialize llm_config to prevent AttributeError
```

2. **Add Null Check** (configuration_internvl_chat.py:85)
```python
output['llm_config'] = self.llm_config.to_dict() if self.llm_config is not None else {}
```

#### Root Cause Analysis
When executing:
```python
model = AutoModel.from_pretrained(model_path, trust_remote_code=True).half().cuda().to(torch.bfloat16)
```

The following occurs:
1. The Hugging Face framework downloads and parses `configuration_internvl_chat.py`
2. During config initialization (`transformers/configuration_utils.py:816-822`):
```python
config_dict = self.to_dict()

# Get the default config dict (from a fresh PreTrainedConfig instance)
default_config_dict = PretrainedConfig().to_dict()

# get class specific config dict
class_config_dict = self.__class__().to_dict() if not self.has_no_defaults_at_init else {}
```
3. **Key Issue**:
- `self.llm_config` is `None` during `class_config_dict` generation because `llm_config` is None
- Without explicit initialization, this triggers an `AttributeError` when `.to_dict()` is called

#### Why the Fix Works
1. The initialization ensures `self.llm_config` always exists (even as `None`)
2. The null check prevents method calls on `None` while maintaining expected dictionary structure
---

configuration_internvl_chat.py

@@ -47,6 +47,8 @@ class InternVLChatConfig(PretrainedConfig):
             logger.info('llm_config is None. Initializing the LlamaConfig config with default values (`LlamaConfig`).')
 
         self.vision_config = InternVisionConfig(**vision_config)
+        # Initialize llm_config to prevent AttributeError
+        self.llm_config = None
         if llm_config.get('architectures')[0] == 'LlamaForCausalLM':
             self.llm_config = LlamaConfig(**llm_config)
         elif llm_config.get('architectures')[0] == 'InternLM2ForCausalLM':
@@ -81,7 +83,7 @@ class InternVLChatConfig(PretrainedConfig):
         """
         output = copy.deepcopy(self.__dict__)
         output['vision_config'] = self.vision_config.to_dict()
-        output['llm_config'] = self.llm_config.to_dict()
+        output['llm_config'] = self.llm_config.to_dict() if self.llm_config is not None else {}
         output['model_type'] = self.__class__.model_type
         output['use_backbone_lora'] = self.use_backbone_lora
         output['use_llm_lora'] = self.use_llm_lora