Deploying locally takes the least amount of time when executed through native OS tools.
Carefully read and apply the steps described below.
The engine will automatically fetch large dependencies in the background.
Without any user input, the software calibrates parameters for optimal hardware usage.
The dots.mocr model is a state‑of‑the‑art multimodal OCR system designed for high‑speed document processing. It combines vision and language modules to extract text from scanned images, handwritten notes, and natural‑scene photos with unprecedented accuracy. With a parameter count of 1.5 B, the model runs efficiently on consumer GPUs while maintaining real‑time inference speeds. The architecture incorporates a novel attention‑based layout analyzer that preserves structural relationships, enabling downstream tasks such as data entry and content summarization. dots.mocr also supports multilingual scripts, achieving over 90 % word‑error‑rate reduction on benchmark datasets compared to legacy solutions. Its modular design allows developers to fine‑tune specific components, making it a versatile choice for enterprise workflow automation.
| Spec | Value |
|---|---|
| Parameters | 1.5 B |
| Input Types | PDF, JPG, PNG, Handwritten |
| Supported Languages | 100 |
| Inference Speed | >30 fps on RTX 3080 |
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