frostedunicorn/logos-v61-sft
frostedunicorn/logos-v61-sft is a 7.6 billion parameter research-grade language model, fine-tuned from Qwen2.5-7B-Instruct, specializing in Abrahamic religious texts across Arabic, Hebrew, Greek, English, and Latin. It is designed for multilingual text understanding, verse recall, and cross-tradition comparison within religious contexts. The model is optimized for research into religious text processing and understanding, not for authoritative interpretation or advice.
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Logos v6.1-SFT: Abrahamic Religious Texts Model
Logos v6.1-SFT is a 7.6 billion parameter research-grade language model, fine-tuned from Qwen2.5-7B-Instruct, specifically designed for working with Abrahamic religious texts. It supports multiple languages including Arabic, Hebrew, Greek, English, and Latin, making it a valuable tool for multilingual religious studies.
Key Capabilities
- Multilingual Text Understanding: Processes religious texts across five languages.
- Instruction-Tuned Q&A: Trained on 30K Q&A samples for verse recall, cross-tradition comparison, and tafsir explanation.
- Citation Formatting (Experimental): Includes training on Quran, Bible, and Talmud citation formats, though accuracy is currently low (20%).
- Research Focus: Developed for academic and research purposes in religious text analysis.
Limitations and Considerations
It is crucial to note that Logos v6.1-SFT is a research alpha model with known limitations. It exhibits low citation accuracy (20%), zero exact verse recall (relies on RAG), and a 50% hallucination rate, making it unsuitable for production factual queries or authoritative religious advice. The model has not memorized verse text and does not provide scholarly-grade Arabic diacritics. Users should be aware of these constraints and use the model strictly for research and experimental purposes.