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	Update app.py
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        app.py
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    | @@ -4,19 +4,29 @@ import bitsandbytes | |
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            import accelerate
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            import scipy
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            from PIL import Image
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            -
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            from transformers import Blip2Processor, Blip2ForConditionalGeneration, InstructBlipProcessor, InstructBlipForConditionalGeneration
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            def load_caption_model(blip2=False, instructblip=True):
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                if blip2:
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                    processor = Blip2Processor.from_pretrained("Salesforce/blip2-opt-2.7b", load_in_8bit=True,torch_dtype=torch.float16)
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                    model = Blip2ForConditionalGeneration.from_pretrained("Salesforce/blip2-opt-2.7b", load_in_8bit=True,torch_dtype=torch.float16)
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                    #model = Blip2ForConditionalGeneration.from_pretrained("Salesforce/blip2-opt-2.7b", torch_dtype=torch.float16, device_map="auto")
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                if instructblip:
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                    model = InstructBlipForConditionalGeneration.from_pretrained("Salesforce/instructblip-vicuna-7b", load_in_8bit=True,torch_dtype=torch.float16)
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                    processor = InstructBlipProcessor.from_pretrained("Salesforce/instructblip-vicuna-7b", load_in_8bit=True,torch_dtype=torch.float16)
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                return model, processor
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            import accelerate
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            import scipy
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            from PIL import Image
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            import torch.nn as nn
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            from transformers import Blip2Processor, Blip2ForConditionalGeneration, InstructBlipProcessor, InstructBlipForConditionalGeneration
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            def load_caption_model(blip2=False, instructblip=True):
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            model = YourModel()
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                if blip2:
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                    processor = Blip2Processor.from_pretrained("Salesforce/blip2-opt-2.7b", load_in_8bit=True,torch_dtype=torch.float16)
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                    model = Blip2ForConditionalGeneration.from_pretrained("Salesforce/blip2-opt-2.7b", load_in_8bit=True,torch_dtype=torch.float16)
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                    if torch.cuda.device_count() > 1:
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                        model = nn.DataParallel(model)
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                        model.to('cuda')
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                    #model = Blip2ForConditionalGeneration.from_pretrained("Salesforce/blip2-opt-2.7b", torch_dtype=torch.float16, device_map="auto")
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                if instructblip:
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                    model = InstructBlipForConditionalGeneration.from_pretrained("Salesforce/instructblip-vicuna-7b", load_in_8bit=True,torch_dtype=torch.float16)
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                    if torch.cuda.device_count() > 1:
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                        model = nn.DataParallel(model)
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                        model.to('cuda')
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                    processor = InstructBlipProcessor.from_pretrained("Salesforce/instructblip-vicuna-7b", load_in_8bit=True,torch_dtype=torch.float16)
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                return model, processor
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