Upload modeling_mic21.py with huggingface_hub

modeling_mic21.py

@@ -13,17 +13,24 @@ class MIC21SummarizerModel(PreTrainedModel):
     model_parallel = True
     place_model_on_device = False
     model_wrapped = {}
+
+    def init_components(self):
+        self.components["image_model"] = ResNetForImageClassification.from_pretrained(config.hf_image_model).cuda()
+        self.components["image_processor"] = AutoImageProcessor.from_pretrained(config.hf_image_model)
+        
+        self.components["llm"] = AutoModelForCausalLM.from_pretrained(config.hf_text_model,torch_dtype=torch.float16).cuda()
+        self.components["tokenizer"] = AutoTokenizer.from_pretrained(config.hf_text_model)
     
     def __init__(self,config):
         super().__init__(config)
         #Init Image Processing Model        
         self.components = {"image_model":None,"llm":None,"tokenizer":None,"image_processor":None}
         #self.components["image_model"] = ResNetForImageClassification.from_pretrained(config.hf_image_model,device_map=f"cuda:{config.im_model_cuda_id}")
-        self.components["image_model"] = ResNetForImageClassification.from_pretrained(config.hf_image_model).cpu().cuda()
+        #self.components["image_model"] = ResNetForImageClassification.from_pretrained(config.hf_image_model).cpu().cuda()
         
-        self.components["image_processor"] = AutoImageProcessor.from_pretrained(config.hf_image_model)
+        #self.components["image_processor"] = AutoImageProcessor.from_pretrained(config.hf_image_model)
 
-        self.components["llm"] = AutoModelForCausalLM.from_pretrained(config.hf_text_model,torch_dtype=torch.float16).cpu().cuda()
+        #self.components["llm"] = AutoModelForCausalLM.from_pretrained(config.hf_text_model,torch_dtype=torch.float16).cpu().cuda()
         
         #self.quantization_config = BitsAndBytesConfig(load_in_4bit=True,bnb_4bit_compute_dtype=torch.bfloat16)
         #self.components["llm"] = AutoModelForCausalLM.from_pretrained(
@@ -34,7 +41,7 @@ class MIC21SummarizerModel(PreTrainedModel):
         #    attn_implementation=config.attn_implementation,
         #    #quantization_config=self.quantization_config
         #)
-        self.components["tokenizer"] = AutoTokenizer.from_pretrained(config.hf_text_model)
+        #self.components["tokenizer"] = AutoTokenizer.from_pretrained(config.hf_text_model)
 
         #self.in_device = config.in_device
         #self.out_device = config.out_device