Push model using huggingface_hub.

mini_gpt4_llama_v2.py

@@ -29,6 +29,7 @@ from transformers import PretrainedConfig
 from transformers import PreTrainedModel
 from typing import List
 from collections import defaultdict
+from minigpt4_video.conversation import CONV_VISION
 class minigpt4_video_config(PretrainedConfig):
     model_type="minigpt4_video"
     PRETRAINED_MODEL_CONFIG_DICT = {
@@ -74,6 +75,7 @@ class MiniGPT4_Video(Blip2Base, PreTrainedModel):
         vis_processor_cfg = {"name": "blip2_image_train","image_size": 224}
         print(vis_processor_cfg)
         self.vis_processor = registry.get_processor_class(vis_processor_cfg["name"]).from_config(vis_processor_cfg)
+        self.CONV_VISION = CONV_VISION
         if "Mistral" in self.llama_model:
             from minigpt4_video.modeling_mistral import MistralForCausalLM as llm_model
             print("Mistral model")