naver-clova-ix/donut-base-finetuned-docvqa
Primitive: /extract · Extract ·
Encoder-Decoder
Donut model fine-tuned on DocVQA. It was introduced in the paper OCR-free Document Understanding Transformer by Geewok et al. and first released in this repository.
MultimodalText regions
Overview
Hardware: — drives latency, throughput & cost
| Size | 110M params |
|---|---|
| Tasks | /extract |
| License | mit |
| Latency | 6.9 s |
| Throughput | 87 tok/s |
| Cost | $2.56 /1M tok |
Cost is approximate — computed from list GPU prices; your actual price depends on the provider you deploy SIE with.
Extraction
| Output kinds | text_regions |
|---|---|
| Inputs | image |
| Max sequence length | — |
Benchmarks
DocVQA
Visual question answering on document images
Corpus: 5,188 Queries: 5,188
Quality
anls 0.6350
Performance L4-SPOT b1 c4
Performance L4 b1 c16
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