Model reference · open weights
PP-OCRv5_mobile_rec_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) | 8M |
| Runs with | PaddleOCR |
| Released | 2026-03-18 |
| Popularity | 756 downloads / month |
| Licence | Open weights |
About
PP-OCRv5_mobile_rec is one of the PP-OCRv5_rec that are the latest generation text line recognition models developed by PaddleOCR team. It aims to efficiently and accurately support the recognition of four major languages—Simplified Chinese, Traditional Chinese, English, and Japanese—as well as complex text scenarios such as handwriting, vertical text, pinyin, and rare characters using a single model. 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.4166 | 0.4944 | 0.8605 | 0.8753 | 0.7199 | 0.5786 | 0.7577 | 0.5570 | 0.7703 | 0.7248 | 0.8089 | 0.5398 | 0.8015 |
Note: If any character (including punctuation) in a line is incorrect, the entire line is marked as wrong. This ensures higher accuracy in practical applications.
import requests
from PIL import Image
from transformers import AutoImageProcessor, AutoModelForTextRecognition
model_path = "PaddlePaddle/PP-OCRv5_mobile_rec_safetensors"
model = AutoModelForTextRecognition.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_rec_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_text_recognition(outputs)
for result in results:
print(result)
From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Once AxForge deploys pp-ocrv5-mobile-rec-safetensors for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (pp-ocrv5-mobile-rec-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-rec-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.