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add decorator to functions
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app.py
CHANGED
@@ -45,37 +45,38 @@ aihub_deplot_model_path='./deplot_k.pt'
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t5_model_path = './ke_t5.pt'
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# Load first model ko-deplot
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processor1 = Pix2StructProcessor.from_pretrained('nuua/ko-deplot')
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model1 = Pix2StructForConditionalGeneration.from_pretrained('nuua/ko-deplot')
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@spaces.GPU(enable_queue=True)
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model1.
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# Load second model aihub-deplot
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processor2 = AutoProcessor.from_pretrained("ybelkada/pix2struct-base")
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model2 = Pix2StructForConditionalGeneration.from_pretrained("ybelkada/pix2struct-base")
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@spaces.GPU(enable_queue=True)
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tokenizer = T5Tokenizer.from_pretrained("KETI-AIR/ke-t5-base")
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t5_model = T5ForConditionalGeneration.from_pretrained("KETI-AIR/ke-t5-base")
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@spaces.GPU(enable_queue=True)
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t5_model.load_state_dict(torch.load(t5_model_path, map_location=device))
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@spaces.GPU(enable_queue=True)
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model2.to(device)
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@spaces.GPU(enable_queue=True)
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t5_model.to(device)
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#Load third model unichart
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unichart_model_path = "./unichart"
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model3 = VisionEncoderDecoderModel.from_pretrained(unichart_model_path)
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processor3 = DonutProcessor.from_pretrained(unichart_model_path)
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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@spaces.GPU(enable_queue=True)
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#ko-deplot 추론함수
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# Function to format output
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t5_model_path = './ke_t5.pt'
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# Load first model ko-deplot
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@spaces.GPU(enable_queue=True)
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def load_model1():
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processor1 = Pix2StructProcessor.from_pretrained('nuua/ko-deplot')
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model1 = Pix2StructForConditionalGeneration.from_pretrained('nuua/ko-deplot')
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model1.load_state_dict(torch.load(ko_deplot_model_path, map_location=device))
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model1.to(device)
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return processor1,model1
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processor1,model1=load_model1()
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# Load second model aihub-deplot
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@spaces.GPU(enable_queue=True)
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def load_model2():
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processor2 = AutoProcessor.from_pretrained("ybelkada/pix2struct-base")
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model2 = Pix2StructForConditionalGeneration.from_pretrained("ybelkada/pix2struct-base")
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model2.load_state_dict(torch.load(aihub_deplot_model_path, map_location=device))
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model2.to(device)
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return processor2,model2
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processor2,model2=load_model2()
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#Load third model unichart
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@spaces.GPU(enable_queue=True)
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def load_model3():
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unichart_model_path = "./unichart"
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model3 = VisionEncoderDecoderModel.from_pretrained(unichart_model_path)
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processor3 = DonutProcessor.from_pretrained(unichart_model_path)
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model3.to(device)
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return processor3,model3
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processor3,model3=load_model3()
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#ko-deplot 추론함수
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# Function to format output
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