content: def load_text_model(prefix, config, weights, name=None):
      if config.model_type == "llama":
          from lorax_server.models.custom_modeling.flash_llama_modeling import (
              FlashLlamaForCausalLM,
          )
  
          return FlashLlamaForCausalLM(prefix, config, weights)
      elif config.model_type == "mistral":
          from lorax_server.models.custom_modeling.flash_mistral_modeling import (
              FlashMistralForCausalLM,
          )
  
          return FlashMistralForCausalLM(prefix, config, weights, name=name)
      elif config.model_type == "gemma":
          from lorax_server.models.custom_modeling.flash_gemma_modeling import (
              FlashGemmaForCausalLM,
          )
  
          return FlashGemmaForCausalLM(prefix, config, weights, causal=False)
      elif config.model_type == "paligemma":
          from lorax_server.models.custom_modeling.flash_gemma_modeling import (
              FlashGemmaForCausalLM,
          )
  
          return FlashGemmaForCausalLM(prefix, config, weights)
      else:
          raise RuntimeError(f"Unsupported model type {config.model_type}")
  
  
  def load_vision_model(prefix, config, weights):
      if config.model_type == "clip_vision_model":
          from lorax_server.models.custom_modeling.clip import (
              CLIPVisionTransformer,
          )
  
          return CLIPVisionTransformer(prefix=f"{prefix}.vision_model", config=config, weights=weights)
      if config.model_type == "siglip_vision_model":
          from lorax_server.models.custom_modeling.siglip import (
              SiglipVisionTransformer,
          )
  
          return SiglipVisionTransformer(prefix="vision_tower.vision_model", config=config, weights=weights)
      else:
          raise RuntimeError(f"Unsupported model type {config.model_type}")
  