PP-OCRv6 medium recognizer — CrispEmbed GGUF
Files: PP-OCRv6_medium_rec-f16.gguf, PP-OCRv6_medium_rec-f32.gguf,
PP-OCRv6_medium_rec-q8-head.gguf, and
PP-OCRv6_medium_rec-crispasr-q4_k-policy.gguf.
The policy-q4 container intentionally keeps the complete PP-OCRv6 recognizer graph in F16: quantizing intermediate CNN/SVTR weights caused compounding CTC drift. Source: PaddlePaddle PP-OCRv6, Apache-2.0.
The native F32 conversion matches the reference through logits (cosine 1.0). The published F16 artifact is an inference-speed artifact, not a parity claim: repeated half-precision layers accumulate measurable drift, so production quality should use the Q8/F32-quality policy artifact once published.
q8-head is built from F32 and quantizes only the final SVTR/CTC head;
measured logits cosine is 0.999934.
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 — where it is documented at all — 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.
