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	Create DeepSeek-OCR-vllm/config.py
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        DeepSeek-OCR-master/DeepSeek-OCR-vllm/config.py
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            # TODO: change modes
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            # Tiny: base_size = 512, image_size = 512, crop_mode = False
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            # Small: base_size = 640, image_size = 640, crop_mode = False
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            # Base: base_size = 1024, image_size = 1024, crop_mode = False
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            # Large: base_size = 1280, image_size = 1280, crop_mode = False
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            # Gundam: base_size = 1024, image_size = 640, crop_mode = True
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            BASE_SIZE = 1024
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            IMAGE_SIZE = 640
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            CROP_MODE = True
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            MIN_CROPS= 2
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            MAX_CROPS= 6 # max:9; If your GPU memory is small, it is recommended to set it to 6.
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            MAX_CONCURRENCY = 100 # If you have limited GPU memory, lower the concurrency count.
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            NUM_WORKERS = 64 # image pre-process (resize/padding) workers 
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            PRINT_NUM_VIS_TOKENS = False
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            SKIP_REPEAT = True
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            MODEL_PATH = 'deepseek-ai/DeepSeek-OCR' # change to your model path
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            # TODO: change INPUT_PATH
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            # .pdf: run_dpsk_ocr_pdf.py; 
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            # .jpg, .png, .jpeg: run_dpsk_ocr_image.py; 
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            # Omnidocbench images path: run_dpsk_ocr_eval_batch.py
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            INPUT_PATH = '' 
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            OUTPUT_PATH = ''
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            PROMPT = '<image>\n<|grounding|>Convert the document to markdown.'
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            # PROMPT = '<image>\nFree OCR.'
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            # TODO commonly used prompts
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            # document: <image>\n<|grounding|>Convert the document to markdown.
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            # other image: <image>\n<|grounding|>OCR this image.
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            # without layouts: <image>\nFree OCR.
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            # figures in document: <image>\nParse the figure.
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            # general: <image>\nDescribe this image in detail.
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            # rec: <image>\nLocate <|ref|>xxxx<|/ref|> in the image.
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            # '先天下之忧而忧'
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            # .......
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            from transformers import AutoTokenizer
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            TOKENIZER = AutoTokenizer.from_pretrained(MODEL_PATH, trust_remote_code=True)
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