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cstr/PP-OCRv6-tiny-det-GGUF overview

PP OCRv6 tiny detector — CrispEmbed GGUF Files: PP OCRv6 tiny det f16.gguf and PP OCRv6 tiny det crispasr q4 k policy.gguf . The detector path is kept at F16 i…

crispembedggufocrpp-ocrv6license:apache-2.0region:us

Runs locally from ~0.8 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

2 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
PP-OCRv6_tiny_det-crispasr-q4_k-policy.ggufGGUFQ4_K0.8 MBDownload
PP-OCRv6_tiny_det-f16.ggufGGUFF160.8 MBDownload

Model Details

Model IDcstr/PP-OCRv6-tiny-det-GGUF
Authorcstr
Pipeline
Licenseapache-2.0
Base model
Last modified2026-08-02T15:16:31.000Z

Model README

---

library_name: crispembed

license: apache-2.0

tags: [ocr, pp-ocrv6, gguf, crispembed]

---

PP-OCRv6 tiny detector — CrispEmbed GGUF

Files: PP-OCRv6_tiny_det-f16.gguf and PP-OCRv6_tiny_det-crispasr-q4_k-policy.gguf.

The detector path is kept at F16 in the q4-policy artifact for output parity. crispembed-diff final probability-map cosine: 0.999997616.

Source: PaddlePaddle PP-OCRv6, Apache-2.0. Large files are generated and tested with CrispEmbed’s PP-OCRv6 runtime.

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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