Update donut_inference.py
Browse files- donut_inference.py +3 -3
donut_inference.py
CHANGED
@@ -10,10 +10,10 @@ load_dotenv()
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# imgae = image.resize((1864, 1440))
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device = "cuda" if torch.cuda.is_available() else "cpu"
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device = "cpu"
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# Load the processor from the local directory
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processor = DonutProcessor.from_pretrained("Henge-navuuu/donut-base-finetuned-forms-v1")
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# Load the model from the local directory
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model = VisionEncoderDecoderModel.from_pretrained("Henge-navuuu/donut-base-finetuned-forms-v1")
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model.to(device)
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@@ -25,7 +25,7 @@ def inference(image):
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decoder_input_ids = processor.tokenizer(task_prompt, add_special_tokens=False, return_tensors="pt")["input_ids"]
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# device = "cuda" if torch.cuda.is_available() else "cpu"
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model.to(device)
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outputs = model.generate(pixel_values.to(device),
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decoder_input_ids=decoder_input_ids.to(device),
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# imgae = image.resize((1864, 1440))
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device = "cuda" if torch.cuda.is_available() else "cpu"
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# device = "cpu"
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# Load the processor from the local directory
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processor = DonutProcessor.from_pretrained("Henge-navuuu/donut-base-finetuned-forms-v1")
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processor.to(device)
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# Load the model from the local directory
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model = VisionEncoderDecoderModel.from_pretrained("Henge-navuuu/donut-base-finetuned-forms-v1")
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model.to(device)
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decoder_input_ids = processor.tokenizer(task_prompt, add_special_tokens=False, return_tensors="pt")["input_ids"]
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# device = "cuda" if torch.cuda.is_available() else "cpu"
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# model.to(device)
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outputs = model.generate(pixel_values.to(device),
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decoder_input_ids=decoder_input_ids.to(device),
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