souvik3333

5 ms·

1.
by souvik3333 11mo ago
We have evaluated against Gemini-2.5-flash. You can check the benchmarks here https://nanonets.com/research/nanonets-ocr-2/#markdown-evalu...
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by souvik3333 11mo ago
Yeah, we do have api support. Currently, you can process 10k documents per month free. Let me know if you face any issues.
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Show HN: DocStrange: An LLM-Ready Data Platform That Performs Better Than Gemini(docstrange.nanonets.com)
5 points by souvik3333 11mo ago|5 comments
4.
by souvik3333 11mo ago
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 from the demo. HF: https://huggingface.co/nanon
5.
by souvik3333 1y ago
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.
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by souvik3333 1y ago
This is the result. ``` Page 1 of 1 Page # <page_number>8</page_number> Log: MA 6100 Z. O 3. 15 <table> <tr> <td>34</td> <td>cement emitter resistors -</t
7.
by souvik3333 1y ago
They will be extracted in a new line as normal text. It will be the last line.
8.
by souvik3333 1y ago
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 instead of markdown.
9.
by souvik3333 1y ago
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, figures, and so on) will be described within the `<img>` t
10.
by souvik3333 1y ago
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. https://ibb.co/C36RRjYs Regarding the token lim
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by souvik3333 1y ago
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 your files, there is a huggingface demo, you can quickly test t
12.
by souvik3333 1y ago
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 and various European languages. Additionally, the base model (
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by souvik3333 1y ago
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 to markdown as a task. The problem with eval
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by souvik3333 1y ago
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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Gemini-2.5-pro-preview-06-05 performance on IDP Leaderboard(idp-leaderboard.org)
2 points by souvik3333 1y ago|0 comments
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Show HN: onprem unstructured data extraction with 4 lines of code(github.com)
8 points by souvik3333 1y ago|0 comments