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Nanonets-OCR-s – OCR model that transforms documents into structured markdown

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Re: Nanonets-OCR-s – OCR model that transforms documents into structured markdown

#11

Post by wickedsight »

silversmith wrote: post #3

I'm curious, how does it do with non-english texts? It's my understanding that LLM-based OCR solutions fall way behind traditional ones once you introduce other languages.

Understanding or experience?

Because my experience is not at all like that. If I use both Google Translate and ChatGPT on an image, ChatGPT is pretty much always better. It can even translate Japanese hand written menus quite well. With the added benefit of it being able to add context and explain what the dishes are.

Re: Nanonets-OCR-s – OCR model that transforms documents into structured markdown

#12

Post by [deleted] »

souvik3333 wrote: post #8
progval wrote: post #6

It's not open-source (nor open-weight): https://huggingface.co/nanonets/Nanonets-OCR-s/discussions/2

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

[deleted]

Re: Nanonets-OCR-s – OCR model that transforms documents into structured markdown

#13

Post by gardnr »

souvik3333 wrote: post #8
progval wrote: post #6

It's not open-source (nor open-weight): https://huggingface.co/nanonets/Nanonets-OCR-s/discussions/2

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

Interestingly, another OCR model based on Qwen2.5-VL-3B just dropped which also publishes as Apache 2. It's right next to Nanonets-OCR-s on the HF "Trending" list.

https://huggingface.co/echo840/MonkeyOCR/blob/main/Recogniti...

Re: Nanonets-OCR-s – OCR model that transforms documents into structured markdown

#15

Post by silversmith »

wickedsight wrote: post #11
silversmith wrote: post #3

I'm curious, how does it do with non-english texts? It's my understanding that LLM-based OCR solutions fall way behind traditional ones once you introduce other languages.

Understanding or experience? Because my experience is not at all like that. If I use both Google Translate and ChatGPT on an image, ChatGPT is pretty much always better. It can even translate Japanese hand written menus quite well. With the added benefit of it being able to add context and explain what the dishes are.

I'm passively interested in small, local LLM OCR, due to couple ideas kicking around between my ears. Tried some a while ago, but most of my recent knowledge is second-hand. Waiting for someone to exclaim "hey this works now!" before committing more time :)

With the big commercial offerings like chatgpt I'd fully expect them to work fine, due to the absolutely massive horsepower in use.

Re: Nanonets-OCR-s – OCR model that transforms documents into structured markdown

#16

Post by souvik3333 »

Eisenstein wrote: post #14

How does it do with handwriting?

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.

Re: Nanonets-OCR-s – OCR model that transforms documents into structured markdown

#17

Post by Eisenstein »

souvik3333 wrote: post #16
Eisenstein wrote: post #14

How does it do with handwriting?

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.

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?

Re: Nanonets-OCR-s – OCR model that transforms documents into structured markdown

#19

Post by mvac »

PixelPanda wrote: post #2

Full disclaimer: I work at Nanonets Excited to share Nanonets-OCR-s, a powerful and lightweight (3B) VLM model that converts documents into clean, structured Markdown. This model is trained to understand document structure and content context (like tables, equations, images, plots, watermarks, checkboxes, etc.). Key Features: LaTeX Equation Recognition Converts inline and block-level math into properly formatted LaTe…

Correct link for Docext: https://github.com/NanoNets/docext/blob/main/PDF2MD_README.m...

Re: Nanonets-OCR-s – OCR model that transforms documents into structured markdown

#20

Post by souvik3333 »

Eisenstein wrote: post #17
souvik3333 wrote: post #16

Earlier quoted context omitted.

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.

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?

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.

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