MAEUM AI ENGINE (TRUTHFUL) - macOS Version This package provides the Truthful version of MAEUM AI for macOS. It’s designed for running the AI engine locally and offers a streamlined experience for users.

πŸ“¦ Contents:

MaeumAI: The main executable file – the core AI engine. koboldcpp-mac-arm64: A backend engine optimized for running Large Language Models (LLMs). models/: Contains the AI model files in GGUF format (.gguf). These are essential for the AI to function. _internal/: Internal libraries required for the program's operation – do not delete. πŸš€ Getting Started

Method 1: Recommended - Terminal Execution

Using the terminal provides the easiest way to troubleshoot any issues.

Open the Terminal application. Navigate to the folder containing this package using the cd command. Drag the folder directly into the Terminal window to automatically paste the path. bash cd /path/to/extracted/folder

Run the AI engine with the following command: bash ./MaeumAI

Method 2: Double-Click Execution

You can also run the AI engine by double-clicking the MaeumAI icon in Finder. (Initial execution may be blocked due to security settings.)

⚠️ Troubleshooting

"Unable to open because the developer cannot be verified" Error: In Finder, right-click (or Control+click) on the MaeumAI file. Select β€œOpen” from the menu. Click β€œOpen” again in the warning dialog box. (This may only need to be done once for subsequent double-clicks.) koboldcpp Permissions Error: The koboldcpp-mac-arm64 file might require execute permissions. Run the following command in the Terminal: bash chmod +x koboldcpp-mac-arm64

Model File Not Recognized: Ensure that the models folder contains .gguf extension files – these are the necessary AI model files. Created by MAEUM AI Team (Lee, DongHun)

MAEUM AI ENGINE (TRUTHFUL) - macOS Version 이 ν”„λ‘œκ·Έλž¨μ€ MAEUM AI의 Truthful 버전을 μ‹€ν–‰ν•˜κΈ° μœ„ν•œ νŒ¨ν‚€μ§€μž…λ‹ˆλ‹€.

πŸ“‹ κ΅¬μ„±ν’ˆ MaeumAI: μ‹€ν–‰ 파일 (μ‹€μ œ AI μ—”μ§„) koboldcpp-mac-arm64: LLM ꡬ동을 μœ„ν•œ λ°±μ—”λ“œ μ—”μ§„ models/: AI λͺ¨λΈ νŒŒμΌλ“€ (.gguf) _internal/: ν”„λ‘œκ·Έλž¨ 싀행에 ν•„μš”ν•œ λΌμ΄λΈŒλŸ¬λ¦¬λ“€ (μ‚­μ œ κΈˆμ§€) πŸš€ μ‹€ν–‰ 방법 방법 1: ν„°λ―Έλ„μ—μ„œ μ‹€ν–‰ (ꢌμž₯) 였λ₯˜ λ©”μ‹œμ§€λ₯Ό ν™•μΈν•˜κΈ° μ‰¬μ›Œ κ°€μž₯ ꢌμž₯λ˜λŠ” λ°©λ²•μž…λ‹ˆλ‹€.

터미널(Terminal) 앱을 μ—½λ‹ˆλ‹€. cd λͺ…λ Ήμ–΄λ‘œ 이 ν΄λ”λ‘œ μ΄λ™ν•©λ‹ˆλ‹€. (폴더λ₯Ό 터미널 창으둜 λ“œλž˜κ·Έν•˜λ©΄ κ²½λ‘œκ°€ μž…λ ₯λ©λ‹ˆλ‹€) cd /path/to/extracted/folder μ•„λž˜ λͺ…λ Ήμ–΄λ‘œ μ‹€ν–‰ν•©λ‹ˆλ‹€. ./MaeumAI 방법 2: 더블 클릭 μ‹€ν–‰ Finderμ—μ„œ MaeumAI μ•„μ΄μ½˜μ„ 더블 ν΄λ¦­ν•˜μ—¬ μ‹€ν–‰ν•  수 μžˆμŠ΅λ‹ˆλ‹€. (λ³΄μ•ˆ 섀정에 따라 μ²˜μŒμ— 싀행이 차단될 수 μžˆμŠ΅λ‹ˆλ‹€)

⚠️ 문제 ν•΄κ²° "개발자λ₯Ό 확인할 수 μ—†κΈ° λ•Œλ¬Έμ— μ—΄ 수 μ—†μŠ΅λ‹ˆλ‹€" λ©”μ‹œμ§€κ°€ λœ¨λŠ” 경우 Finderμ—μ„œ MaeumAI νŒŒμΌμ„ '우클릭' (λ˜λŠ” Control+클릭) ν•©λ‹ˆλ‹€. λ©”λ‰΄μ—μ„œ μ—΄κΈ°λ₯Ό μ„ νƒν•©λ‹ˆλ‹€. κ²½κ³ μ°½μ—μ„œ μ—΄κΈ°λ₯Ό λ‹€μ‹œ ν•œλ²ˆ ν΄λ¦­ν•©λ‹ˆλ‹€. (ν•œ 번만 μ΄λ ‡κ²Œ ν•˜λ©΄ μ΄ν›„μ—λŠ” 더블 클릭으둜 μ‹€ν–‰ κ°€λŠ₯ν•©λ‹ˆλ‹€) koboldcpp κΆŒν•œ 였λ₯˜ koboldcpp-mac-arm64 νŒŒμΌλ„ μ‹€ν–‰ κΆŒν•œμ΄ ν•„μš”ν•  수 μžˆμŠ΅λ‹ˆλ‹€. ν„°λ―Έλ„μ—μ„œ λ‹€μŒμ„ μž…λ ₯ν•˜μ„Έμš”:

chmod +x koboldcpp-mac-arm64 λͺ¨λΈ 파일 인식 λΆˆκ°€ models 폴더 μ•ˆμ— .gguf ν™•μž₯자λ₯Ό κ°€μ§„ λͺ¨λΈ 파일이 μžˆλŠ”μ§€ ν™•μΈν•˜μ„Έμš”.

Created by MAEUM AI Team (Lee, DongHun)


πŸš€ MAEUM-4B Official Release [Headline] [MAEUM-4B Basic Architecture Release] Sharing Benchmark Report (v1.0.0): Proving Inference Integrity through Architecture

[Body] I am excited to share the benchmark report conducted last December, which includes a comprehensive 68-item evaluation to validate the initial performance of the MAEUM-4B model. (Available for download now.)

My focus was not merely on inflating leaderboard metrics, but on demonstrating how a small-scale model can deliver "Truthful" responses within a production-ready architectural environment.

πŸ“Š v1.0.0 Key Metrics:

Reasoning (BBH): 100% (Outperforming frontier models like GPT-4o at 87.3%) *Note: BBH results are subject to environment-specific verification.

Truthfulness (TruthfulQA): 80% (Minimizing hallucinations and securing reliability)

Korean Proficiency (KMMLU/KoBEST): 96% / 94% (Optimized for Korean linguistic nuance)

πŸ› οΈ Architect’s Reflection: These results are the outcome of the initial prototype for my Runtime Bridge Architecture. This milestone confirms that high-performance inference is fully achievable within a compact, ~3GB standalone binary.

While these measurements date back to late last year, they served as the foundation for the newly released v1.0. This official version features enhanced macOS notarization and improved runtime stability.

I will continue to refine this system to be even more robust and user-friendly, moving beyond past figures to build truly reliable AI infrastructure.

πŸ”— Download & Full Report (Hugging Face): https://huggingface.co/princepslee/MAEUM_OS_Truthful_Lite_v1.0_4B_4bit

#GenerativeAI #SystemArchitecture #LLM #Benchmark #MAEUM #OpenSource #InferenceOptimization #Gemma2 #TruthfulAI #GoogleCloud #FSA #SoftwareEngineering #AIInfrastructure #MachineLearning #TechReport

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