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### 请提出你的问题 Not: I have start, end value only

### 请提出你的问题 Hi Sir, I am using paddlenlp document intelligence model for image vqa. Please give ideas for these below 3 queries? 1. Model getting two much of memory usage....

In "document intelligence", i have one problem. That is i have a same key in different places in one single image. how to seperate prediction for my requested prompt.

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### 请提出你的问题 city,state,zip. this key present in image both left and right side. left side patient information and right side prescriber informations are available, how to solve this.

How to instruct the model for getting proper key value pair as json format, without getting any other text.

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I need to get json results from the paragraph contains key value pairs, but llam3 instruct model return json format with some unwanted string, how to get proper answer from...

Related to semantic entity relation

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The semantic entity relation model works fine, some key value pair in documents are predicted as only answer, how to fix this issue. How to properly identified questions and answers...

How can you identified rotated image for extracting text using this ocr. Which code can i refer in this github I need rotated angle and how to rotate as proper...

pytesseract.image_to_osd() error

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Config - python3.10 Ubuntu - 22.04 pytesseract - 0.3.10 opencv - 4.5.4.60 tesseract-ocr engine - 4.1.1 Those are my configurations, I have correct orientation image, there is not rotation needed...

[BUG] I am using CamelModel to run the CRAB agent on top of Groq

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### What version of camel are you using? 0.2.1 ### Problem description ValueError: Unexpected argument `logit_bias` is input into Groq model backend. ### Reproducible example code if __name__ == "__main__":...

I have datasets for document visual question answering, how to prepare custom annotations to fine-tune donut model. I don't have any references to prepare custom annotations for it. Share me...

For individual inference return expected result and batched inference returns different results for same prompts - Qwen2-VL-7B

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### Your current environment message = {{"role": "system", "content": system_prompt}, { "role": "user", "content": [ {"type": "image", "image": image_path, "min_pixels": mm_processor_kwargs['min_pixels'], "max_pixels": mm_processor_kwargs['max_pixels'] }, {"type": "text", "text": user_prompt} ] }}...