surya-ocr-2-onnx-fp16-split-canary

Surya OCR 2 ONNX FP16 Split Canary

This repository contains a converted/quantized artifact derived from datalab-to/surya-ocr-2.

What is included

• Source model: datalab-to/surya-ocr-2
• Runtime/format: ONNX Runtime / WebGPU-oriented experimentation
• Quantization: not quantized; FP16 split vision + language last-logits ONNX canary
• Vision weights included: yes, included as surya_vision.onnx
• Created for: local OCR/document-understanding experiments and parity testing

Validation status

Export canary diff vs full PyTorch forward: max_abs_diff = 0.0 for the traced sample.

Known caveats

This is a fixed-shape split export canary, not a complete browser OCR app. The full-graph ONNX benchmark runner stalled during ORT session/generation; a split decode harness is still required.

Files

surya_vision.onnx, surya_language_last_logits.onnx, processor assets, and export_config.json.

Usage

Use the vision ONNX and language last-logits ONNX together with a custom decode loop matching export_config.json shapes.

Provenance

This artifact was generated non-destructively from the original Hugging Face checkpoint. It is not a new fine-tune.

If you need production parity, compare against the original model on your own document distribution before deployment.