Model reference · open weights
PP-OCRv5_mobile_det_safetensors 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 by | Baidu |
|---|---|
| Published under | PaddlePaddle |
| Type | Language models |
| Task | Image→text |
| Parameters (lead) | 4M |
| Runs with | PaddleOCR |
| Released | 2026-01-15 |
| Popularity | 871 downloads / month |
| Licence | Open weights |
About
PP-OCRv5_mobile_det is one of the PP-OCRv5_det series, the latest generation of text detection models developed by the PaddleOCR team. It aims to efficiently and accurately supports the detection of text in diverse scenarios—including handwriting, vertical, rotated, and curved text—across multiple languages such as Simplified Chinese, Traditional Chinese, English, and Japanese. Key features include robust handling of complex layouts, varying text sizes, and challenging backgrounds, making it suitable for practical applications like document analysis, license plate recognition, and scene text detection. The key accuracy metrics are as follow:
| Handwritten Chinese | Handwritten English | Printed Chinese | Printed English | Traditional Chinese | Ancient Text | Japanese | General Scenario | Pinyin | Rotation | Distortion | Artistic Text | Average |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.744 | 0.777 | 0.905 | 0.910 | 0.823 | 0.581 | 0.727 | 0.721 | 0.575 | 0.647 | 0.827 | 0.525 | 0.770 |
import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModelForObjectDetection
model_path="PaddlePaddle/PP-OCRv5_mobile_det_safetensors"
model = AutoModelForObjectDetection.from_pretrained(model_path, device_map="auto")
image_processor = AutoImageProcessor.from_pretrained(model_path)
image = Image.open(requests.get("https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/general_ocr_001.png", stream=True).raw).convert("RGB")
inputs = image_processor(images=image, return_tensors="pt").to(model.device)
outputs = model(**inputs)
results = image_processor.post_process_object_detection(outputs, target_sizes=inputs["target_sizes"])
for result in results:
print(result["boxes"])
print(result["scores"])
From the published model card. Full card on the HuggingFace links in the sidebar.
How it works
Using it via the API
Once AxForge deploys pp-ocrv5-mobile-det-safetensors for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (pp-ocrv5-mobile-det-safetensors 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-ocrv5-mobile-det-safetensors","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.