fix config saving compatibility issue for transformers 4.45+

config = AutoConfig.from_pretrained("OpenGVLab/InternVL2-1B", trust_remote_code=True)
config.save_pretrained("internvl2-1b")

raises error:

if llm_config['architectures'][0] == 'LlamaForCausalLM':
KeyError: 'architectures'

the root cause that transformers added validation of non-default parameters for generation during config saving it requires initialize configuration class without parameters and as the result llm_config comes as None (and according to code above it become {})

configuration_internvl_chat.py

@@ -46,9 +46,9 @@ class InternVLChatConfig(PretrainedConfig):
             logger.info('llm_config is None. Initializing the LlamaConfig config with default values (`LlamaConfig`).')
 
         self.vision_config = InternVisionConfig(**vision_config)
-        if llm_config['architectures'][0] == 'LlamaForCausalLM':
+        if llm_config.get('architectures', ["Qwen2ForCausalLM"])[0] == 'LlamaForCausalLM':
             self.llm_config = LlamaConfig(**llm_config)
-        elif llm_config['architectures'][0] == 'Qwen2ForCausalLM':
+        elif llm_config.get('architectures', ["Qwen2ForCausalLM"])[0] == 'Qwen2ForCausalLM':
             self.llm_config = Qwen2Config(**llm_config)
         else:
             raise ValueError('Unsupported architecture: {}'.format(llm_config['architectures'][0]))