Viewing profile — souvik3333

We have evaluated against Gemini-2.5-flash. You can check the benchmarks here https://nanonets.com/research/nanonets-ocr-2/#markdown-evalu...

Yeah, we do have api support. Currently, you can process 10k documents per month free. Let me know if you face any issues.

We have developed DocStrange to create LLM-ready data from images and PDFs. We have open-sourced a 3B finetuned model also. You can try both the open-sourced and private models fro…

It should work there also. We have trained on research papers with two columns of text. Generally, papers have references as a footer and contains page number.

This is the result. ``` Page 1 of 1 Page # <page_number>8</page_number> Log: MA 6100 Z. O 3. 15 34 cement emitter resistors - 0.33 R SW 5% measure 0.29 R, 0.26 R 35 rep…

They will be extracted in a new line as normal text. It will be the last line.

We have trained the model on tables with hierarchical column headers and with rowspan and colspan >1. So it should work fine. This is the reason we predict the table in HTML instea…

Actually, we have trained the model to convert to markdown and do semantic tagging at the same time. Eg, the equations will be extracted as LaTeX equations, and images (plots, figu…

Hey, the reason for the long processing time is that lots of people are using it, and with probably larger documents. I tested your file locally seems to be working correctly. http…

We have not trained explicitly on handwriting datasets (completely handwritten documents). But, there are lots of forms data with handwriting present in training. So, do try on you…

The model was primarily trained on English documents, which is why English is listed as the main language. However, the training data did include a smaller proportion of Chinese an…

Hi, author of the model here.. We have a benchmark for evaluating VLM on document understanding tasks: https://idp-leaderboard.org/ . But unfortunately, it does not include image t…

Hi, author of the model here. It is an open-weight model, you can download it from here: https://huggingface.co/nanonets/Nanonets-OCR-s

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The traditional pipeline for unstructured data extraction typically follows these steps: 1. Image → OCR Model (e.g., Google Vision) → Layout Model (e.g. Surya) → LLM → Final Answer…