Qari-OCR-0.3-SNAPSHOT-VL-2B-Instruct-merged-GGUF Open Source Model

Qari OCR 0.3 SNAPSHOT VL 2B Instruct Merged GGUF

Developed by mradermacher

This is a statically quantized version based on the Qari-OCR-0.3-SNAPSHOT-VL-2B-Instruct-merged model, mainly used for image-to-text conversion tasks.

Image-to-Text

Transformers

English#Image-to-Text #Static Quantization #English OCR

Downloads 188

Release Time : 6/4/2025

Model Overview

This model is a quantization process of the Qari-OCR model from NAMAA-Space, providing multiple quantization options suitable for different hardware environments and performance requirements.

Model Features

Multiple Quantization Options

Provides multiple quantization types from Q2_K to f16 to meet different hardware environments and performance requirements.

Efficient Inference

The quantized model significantly reduces the computational resource requirements while maintaining high accuracy.

Image-to-Text Conversion

Specifically optimized for the task of extracting text content from images.

Model Capabilities

Image OCR

Text Extraction

English Text Recognition

Use Cases

Document Digitization

Scanned Document Conversion

Convert scanned paper documents into editable text formats.

Image Content Analysis

Text Recognition in Images

Extract text content from photos or screenshots.

🚀 Qari-OCR-0.3-SNAPSHOT-VL-2B-Instruct-merged GGUF Quantization

This project provides static quantizations of the Qari-OCR-0.3-SNAPSHOT-VL-2B-Instruct-merged model, offering various quantization types for efficient usage.

🚀 Quick Start

Model Information

Property	Details
Base Model	NAMAA-Space/Qari-OCR-0.3-SNAPSHOT-VL-2B-Instruct-merged
Language	en
Library Name	transformers
Quantized By	mradermacher
Tags	image-to-text

✨ Features

Static quantizations of the Qari-OCR-0.3-SNAPSHOT-VL-2B-Instruct-merged model.
Multiple quantization types available for different use cases.

📚 Documentation

About

These are static quants of Qari-OCR-0.3-SNAPSHOT-VL-2B-Instruct-merged. Weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link	Type	Size/GB	Notes
GGUF	Q2_K	0.8
GGUF	Q3_K_S	0.9
GGUF	Q3_K_M	0.9	lower quality
GGUF	Q3_K_L	1.0
GGUF	IQ4_XS	1.0
GGUF	Q4_K_S	1.0	fast, recommended
GGUF	Q4_K_M	1.1	fast, recommended
GGUF	Q5_K_S	1.2
GGUF	Q5_K_M	1.2
GGUF	Q6_K	1.4	very good quality
GGUF	Q8_0	1.7	fast, best quality
GGUF	f16	3.2	16 bpw, overkill

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

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