Model reference · open weights
donut is an open-weight language model from naver-clova-ix, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
Donut (base-sized model, pre-trained only) Donut model pre-trained-only. It was introduced in the paper OCR-free Document Understanding Transformer by Geewok et al. and first released in this repository. Disclaimer: The team releasing Donut did not write a model card for this model so this model card has been written by the Hugging Face team. Model description Donut consists of a vision encoder (Swin Transformer) and a text decoder (BART). Given an image, the encoder first encodes the image into a tensor of embeddings (of shape batchsize, seqlen, hiddensize), after which the decoder autoregressively generates text, conditioned on the encoding of the encoder. Intended uses & limitations This model is meant to be fine-tuned on a downstream task, like document image classification or document parsing. See the model hub to look for fine-tuned versions on a task that interests you. How to use We refer to the documentation which includes code examples. BibTeX entry and citation info
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | naver-clova-ix |
|---|---|
| Type | Language models |
| Variants | 1 |
| Runs with | transformers |
| Released | 2022-07-19 |
| Popularity | 55k downloads / month |
| Likes | 254 |
| Licence | Open weights |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| donut-base | — | BF16 | — | — | Weights ↗ |
Using it via the API
Once AxForge deploys donut for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (donut below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/chat/completions \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"donut","messages":[{"role":"user","content":"Hello"}]}'
Licence
Open weights under mit — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗