[souvik3333]

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 there: https://huggingface.co/spaces/Souvik3333/Nanonets-ocr-s

We are currently working on creating completely handwritten document datasets for our next model release.

[Eisenstein]

Document:

* https://imgur.com/cAtM8Qn

Result:

* https://imgur.com/ElUlZys

Perhaps it needed more than 1K tokens? But it took about an hour (number 28 in queue) to generate that and I didn't feel like trying again.

How many tokens does it usually take to represent a page of text with 554 characters?

[souvik3333]

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 limit, it depends on the text. We are using the qwen-2.5-vl tokenizer in case you are interested in reading about it.

You can run it very easily in a Colab notebook. This should be faster than the demo https://github.com/NanoNets/docext/blob/main/PDF2MD_README.m...

There are incorrect words in the extraction, so I would suggest you to wait for the handwritten text model's release.