Model reference · open weights

PP-DocLayout_plus-L_onnx

Available as managed deployment LLMs PaddlePaddle Image→text 1 variants 2k dl/mo

PP-DocLayout_plus-L_onnx is an open-weight language model from PaddlePaddle. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.

Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.

What it is

Released byBaidu
Published underPaddlePaddle
TypeLanguage models
TaskImage→text
Runs withPaddleOCR
Released2026-05-26
Popularity2k downloads / month
LicenceOpen weights

About

What PP-DocLayout_plus-L_onnx is

Introduction

A higher-precision layout area localization model trained on a self-built dataset containing Chinese and English papers, PPT, multi-layout magazines, contracts, books, exams, ancient books and research reports using RT-DETR-L. The layout detection model includes 20 common categories: document title, paragraph title, text, page number, abstract, table, references, footnotes, header, footer, algorithm, formula, formula number, image, table, seal, figure_table title, chart, and sidebar text and lists of references. The key metrics are as follow:

ModelmAP(0.5) (%)
PP-DocLayout_plus-L83.2

Note: the evaluation set of the above precision indicators is the self built version sub area detection data set, including Chinese and English papers, magazines, newspapers, research reports PPT、 1000 document type pictures such as test papers and textbooks.

Read the full model card

Model Usage

Install Dependencies

pip install -U paddleocr
pip install -U onnxruntime-gpu

CLI Usage

paddleocr layout_detection -i ./demo.jpg --model_name PP-DocLayout_plus-L --engine onnxruntime

Python API Usage

from paddleocr import LayoutDetection

model = LayoutDetection(
    model_name="PP-DocLayout_plus-L",
    engine="onnxruntime",
)
output = model.predict("./demo.jpg", batch_size=1)
for res in output:
    res.print()
    res.save_to_img(save_path="./output/")
    res.save_to_json(save_path="./output/res.json")

From the published model card. Full card on the HuggingFace links in the sidebar.

How it works

How language models work

Your prompttext / messagesTransformerattention over tokensNext-token loopgenerate + streamResponsetext · tool callsA language model reads your tokens and predicts the next one, again and again, streaming the reply back.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys pp-doclayout-plus-l-onnx for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (pp-doclayout-plus-l-onnx 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":"pp-doclayout-plus-l-onnx","messages":[{"role":"user","content":"Hello"}]}'

Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.

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