The fastest way to get this model running locally is via Docker.
Simply follow the directions outlined below.
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1-click setup: the app automatically fetches the large weight files.
During setup, the script automatically determines and applies the best settings tailored to your machine.
The PaddleOCR-VL-1.6-GGUF is a state‑of‑the‑art vision‑language model designed for high‑accuracy optical character recognition in multilingual documents. It leverages a transformer‑based encoder‑decoder architecture that jointly processes text and layout information, enabling robust recognition of curved and distorted scripts. The model supports over 100 languages and can handle a wide range of document types, from printed books to handwritten notes. Its quantized GGUF format ensures efficient inference on consumer‑grade hardware while maintaining competitive performance metrics. A built‑in language detection module automatically identifies the script, reducing preprocessing overhead. Users can integrate the model into existing pipelines via simple API calls, benefiting from its low memory footprint and fast loading times.
| Model Name | PaddleOCR-VL-1.6-GGUF |
| Architecture | Transformer‑based encoder‑decoder |
| Supported Languages | 100+ |
| Input Resolution | 1024×1024 pixels |
| Parameter Count | 1.6 B |
| Quantization | GGUF (Q4_K_M) |
| Hardware Requirements | CPU/GPU with ≥4 GB VRAM |
| License | Apache 2.0 |
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