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+ ---
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+ license: apache-2.0
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+ language:
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+ - ar
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+ base_model: Qwen/Qwen3-VL-8B
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+ pipeline_tag: image-to-text
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+ tags:
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+ - gguf
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+ - llama.cpp
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+ - qwen3_vl
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+ - vision-language
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+ - ocr
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+ - document-understanding
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+ - information-extraction
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+ - arabic
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+ - legal-documents
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+ - egypt
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+ ---
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+
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+ # Qwen3-VL-8B Contracts OCR (GGUF)
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+
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+ This repository provides **GGUF quantizations** of **Qwen3-VL-8B-Contracts-OCR**, a fine-tuned vision-language model specialized in extracting structured information from scanned Egyptian company incorporation contracts written in Arabic.
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+
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+ > **The full Transformers version, model card, usage example, training details, and documentation here:**
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+ >
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+ > **https://huggingface.com/a-mo-yehia/Qwen3-VL-8B-Contracts-OCR**
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+
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+ ---
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+
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+ # About
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+
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+ These GGUF files are intended for inference with:
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+
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+ - llama.cpp
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+ - LM Studio (when vision support is available)
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+ - llama-server
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+ - compatible GGUF runtimes
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+
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+ The original fine-tuned model was trained using **Unsloth** on top of **Qwen3-VL-8B**.
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+
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+ ---
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+
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+ # Available Quantizations
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+
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+ | File | Description |
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+ |------|-------------|
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+ | `model_f16.gguf` | Full FP16 precision |
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+ | `model_q8_0.gguf` | 8-bit quantization |
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+ | `model_q4_k_m.gguf` | Recommended balance between quality and speed |
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+ | `mmproj_f16.gguf` | Vision projector (required for image inference) |
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+
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+ ---
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+
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+ # Which Quantization Should I Use?
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+
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+ | Quantization | Recommendation |
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+ |--------------|---------------|
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+ | Q4_K_M | Best overall choice for most users |
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+ | Q8_0 | Better quality with higher memory usage |
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+ | F16 | Maximum quality and accuracy |
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+
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+ ---
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+
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+ # Requirements
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+
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+ For vision inference you **must** load:
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+
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+ - one GGUF model
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+ - `mmproj_f16.gguf`
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+
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+ The vision projector is required for processing images.
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+
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+ ---
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+
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+ # Model Purpose
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+
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+ The model extracts structured information from scanned Egyptian company incorporation contracts, including:
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+
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+ - Company name
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+ - Company type
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+ - Business activities
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+ - Company address
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+ - Capital information
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+ - Partners and shareholders
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+ - Contract articles
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+ - Tables (returned as Markdown)
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+ - Other legal fields
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+
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+ The output is a structured JSON document.
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+
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+ ---
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+
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+ # Language
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+
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+ Arabic
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+
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+ ---
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+
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+ # License
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+
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+ Apache-2.0