Document Models (Pretrained)
Collection
Various pretrained models for analyzing documents. These need to be fine-tuned for a task • 20 items • Updated • 1
donut-base-ascii
This is "naver-clova-ix/donut-base" but with all non-ascii tokens removed. This means the model is good for basic English use cases where the text is primarily a-zA-Z0-9 and basic punctuation.
The original model, "naver-clova-ix/donut-base", did not have a token for "1", so that has also been added. The notebook remove-donut-tokens.ipynb details the whole process.
This has not been trained any more than the original model.
I made a whole video about it: https://youtu.be/Uzr553x1gdM
I did a quick speed test for generation against the default model and using bad_words_ids. The bad_words_ids was only 12k tokens instead of the 30k that were removed and it was still noticeably slower.
Speed script here
Launched with this
| approach | time to generate 10 tokens |
|---|---|
| "naver-clova-ix/donut-base" | 205ms |
"naver-clova-ix/donut-base" + 12k bad_words_ids |
280ms |
| "donut-base-ascii" | 195ms |
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