Sophia-v2

Chaperon-Sophia-v2

An experimental research assistant for archaeology, history, biblical studies, and ancient texts.

Developed by Chaperon GmbH and Lucas Bischof, Sophia-v2 demonstrates a complete end-to-end AI workflow including multimodal data processing, document extraction, dataset generation, LoRA fine-tuning, GGUF deployment, and local AI integration.

Overview

Sophia-v2 is a custom fine-tuned variant of Qwen2.5-7B-Instruct designed to explore historical, textual, archaeological, and religious source material through natural conversation.

The project serves both as a technical showcase of Chaperon GmbH's AI capabilities and as a practical proof-of-concept for domain-specific model adaptation.

Project Goals

This project demonstrates the ability to:

• Process large collections of PDFs
• Extract text from historical documents
• Convert audio and video into training datasets
• Process image-based source material
• Generate structured instruction datasets
• Fine-tune Large Language Models using LoRA
• Merge and deploy custom models
• Publish GGUF models for local inference

Training Sources

The training process included the preparation and processing of curated material related to:

• CDLI Cuneiform Collections
• ETCSL Translations
• Ancient Mesopotamian Literature
• Biblical Texts
• Apocryphal Literature
• Gnostic Literature
• Gospel of Mary
• Pistis Sophia
• Comparative Religion
• Historical Source Material
• Archaeological Research

The focus of Sophia-v2 is source-oriented exploration and discussion rather than authoritative interpretation.

Intended Audience

Sophia-v2 may be useful for:

• Archaeology enthusiasts
• History researchers
• Biblical scholars
• Comparative religion communities
• Independent researchers
• Educational projects
• Digital humanities initiatives

Available Models

Sophia_v2_q5_K_M.gguf

Recommended version for most users.

Provides an excellent balance between quality, performance, and memory usage.

Sophia_v2_f16.gguf

Reference-quality version.

Provides maximum fidelity while requiring significantly more storage and memory.

Technical Specifications

Base Model:

• Qwen/Qwen2.5-7B-Instruct

Training Method:

• Supervised Fine Tuning (SFT)
• LoRA Adaptation
• Model Merge
• GGUF Conversion

Deployment Targets:

• LM Studio
• llama.cpp
• Open WebUI
• KoboldCpp

Limitations

Sophia-v2 is a language model and may:

• Generate incorrect information
• Misinterpret source material
• Produce inaccurate citations
• Present plausible but incorrect conclusions

Users should verify important claims using primary and scholarly sources.

About Chaperon GmbH

Sophia-v2 serves as a public demonstration of the capabilities of Chaperon GmbH in:

• Multimodal data processing
• Knowledge extraction
• AI training pipelines
• Custom model development
• Local AI deployment
• Enterprise AI integration

Credits

Created by:

Lucas Bischof
Chaperon GmbH

Base Model:

Qwen/Qwen2.5-7B-Instruct

GGUF Conversion:

llama.cpp

038febb (Improve model card)