---

license: apache-2.0

tags:

- ocr

- arabic

- gguf

- crispembed

- qwen2-vl

base_model: NAMAA-Space/Qari-OCR-0.2.2.1-VL-2B-Instruct

language: ar

pipeline_tag: image-text-to-text

---

Qari-OCR CrispEmbed GGUF

GGUF conversion of NAMAA-Space/Qari-OCR-0.2.2.1-VL-2B-Instruct (Apache-2.0) for use with CrispEmbed.

Model

Arabic OCR with full diacritics (tashkeel) support. Fine-tuned from Qwen2-VL-2B-Instruct via LoRA (r=16, alpha=16, 324 adapter pairs) on 50K Arabic OCR samples.

• Architecture: Qwen2-VL-2B (32L ViT 1280d + spatial merger + 28L Qwen2 LLM 1536d, GQA 12/2)
• Parameters: 2B
• Performance: WER=0.221, CER=0.059, BLEU=0.597
• Training: 50K Arabic OCR records, 1 epoch, LoRA on attention+MLP

Files

| File | Type | Size |

|------|------|------|

| qari-ocr-2b-f16.gguf | F16 | 4.7 GB |

| qari-ocr-2b-q8_0.gguf | Q8_0 | 2.3 GB |

| qari-ocr-2b-q4_k.gguf | Q4_K | 1.6 GB |

Usage

Uses the same qwen2vl engine as other Qwen2-VL models in CrispEmbed.

Conversion

LoRA adapter merged into full-precision Qwen2-VL-2B-Instruct base weights (324 pairs, tensor-by-tensor), then converted to GGUF via CrispEmbed converter. Quantized with crispembed-quantize (vision weights at Q8_0 floor).

License

Apache-2.0 (NAMAA-Space/Qari-OCR).

Provenance and EU AI Act Art. 53 note

• Upstream model: NAMAA-Space/Qari-OCR-0.2.2.1-VL-2B-Instruct — published by NAMAA-Space.
• 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.