cstr/PP-OCRv6-tiny-rec-GGUF overview
PP OCRv6 tiny recognizer — CrispEmbed GGUF Files: PP OCRv6 tiny rec f16.gguf and PP OCRv6 tiny rec crispasr q4 k policy.gguf . The policy q4 container intentio…
Runs locally from ~2.3 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
Model README
---
library_name: crispembed
license: apache-2.0
tags: [ocr, pp-ocrv6, gguf, crispembed]
---
PP-OCRv6 tiny recognizer — CrispEmbed GGUF
Files: PP-OCRv6_tiny_rec-f16.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).
Canonical CrispEmbed publisher: cstr. Large source and working files are kept on /Volumes/backups/ai/crispembed-gguf/.
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.
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Source: Hugging Face · Compare models