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- Extract text from historical documents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:
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)
