PP-OCRv6 tiny recognizer β€” CrispEmbed GGUF

Files: PP-OCRv6_tiny_rec-f16.gguf, PP-OCRv6_tiny_rec-f32.gguf, PP-OCRv6_tiny_rec-q8-head.gguf, and PP-OCRv6_tiny_rec-crispasr-q4_k-policy.gguf.

The policy-q4 container intentionally keeps the complete PP-OCRv6 detector/recognizer graph in F16: quantizing intermediate CNN/SVTR weights caused compounding CTC drift. Source: PaddlePaddle PP-OCRv6, Apache-2.0.

Parity on tests/regression/images/fox.png using the CrispEmbed diff harness: input 0.999999, stage4 0.999982, head_input 0.999988, logits 0.999992 (F16 and policy-q4; all reported stages pass the 0.999 threshold).

The tiny head-only-Q8 artifact is generated from F32 and retains all quality-sensitive tensors at F32; its CTC head is not Q8-eligible because its input width is 80 rather than a 32-multiple.

Provenance and EU AI Act Art. 53 note

  • Upstream model: PaddlePaddle PP-OCRv6.
  • Upstream licence: apache-2.0. This repository redistributes under the same terms; it grants no rights the upstream licence does not.
  • What was done here: format conversion and/or quantisation only (GGUF). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs.
  • Training data: documented β€” where it is documented at all β€” by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository.
  • Provider status: under Regulation (EU) 2024/1689 the upstream authors remain the provider of this model. Converting the serialisation format does not make this repository the provider of a new general-purpose AI model, and no such claim is made. Questions about training content, copyright policy or model capability belong upstream.
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