nk-alex
nk-alex
Just wondering which is the strategy used to calculate start_offset and end_offset. Given a word start_offset has to be the first character index in the full text and end_offset the...
How to reproduce the behaviour --------- Im trying to import my dataset in JSONL format. My dataset has the following format: `{"text": "....", "meta": [{...}]} ` My uploading cofiguration is...
Hi, my question is related to [this one ](https://github.com/doccano/doccano/issues/386). Is this feature already supported? I'm using doccano to annotate my files and exporting them in .jsonl format. As an output...
Hi, first of all, congratulations for this amazing platform to anyone who has contributed to make it what is today. For years now lichess has become my only chess tool....
I have seen this output with the following execution: Having a container: |Id| Length | Width | Height | | :--- | :---: | :---: | ---: | |1| 12...
My question is related to this [one](https://github.com/NielsRogge/Transformers-Tutorials/issues/203). @NielsRogge answared this: What's typically done is a so-called "sliding window" approach, where you slide windows of 512 tokens across the document (for...
I’m using my own version of SROIE dataset for token classification problem using LayourLMv3. I found out a scenario where some information is repeated throughout the document. Let’s say the...
### Bug description Given an image with text in both directions (horizontal and vertical), I'm not able to extract text Sample image:  ### Code snippet to reproduce the bug...
I'm trying to understand which type of Chromosome should I be considering to solve my problem. In my case, I receive a ingredient stock. Every ingredient has a price and...
Taking as starting point this [notebook](https://github.com/NielsRogge/Transformers-Tutorials/blob/master/LayoutLMv2/FUNSD/True_inference_with_LayoutLMv2ForTokenClassification_%2B_Gradio_demo.ipynb) more specifically, this function: ``` from PIL import ImageDraw draw = ImageDraw.Draw(image) font = ImageFont.load_default() def iob_to_label(label): label = label[2:] if not label: return...