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jayfurzy/paterikon-sft-v1
paterikon-sft-v1 is a text generation model from jayfurzy. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
Single-pass supervised fine-tune of Paterikon-3B on Orthodox Q&A pairs.
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From the Hugging Face model README
Single-pass supervised fine-tune of Paterikon-3B on Orthodox Q&A pairs.
Paterikon-SFT-v1 is the first instruction-tuned checkpoint derived from Paterikon-3B. It was fine-tuned with supervised fine-tuning (SFT) on ~140M tokens of synthetically-generated Orthodox Christian Q&A pairs covering theology, spiritual life, Church Fathers, liturgy, and pastoral guidance.
The base model (Paterikon-3B) already had patristic domain fluency from continued pre-training on 116M tokens of Church Father writings. This SFT pass teaches it to answer questions in a pastoral Orthodox voice with theological accuracy.
| Base model | jayfurzy/paterikon-3b (Qwen2.5-3B CPT) |
| Training | Full fine-tune SFT (TRL) |
| Parameters | 3.09 billion |
| Architecture | Qwen2ForCausalLM, 36 layers, 2048 hidden |
| Languages | English (primary), Russian, Greek |
| Training data | ~140M tokens synthetic Orthodox Q&A pairs |
| Frameworks | TRL 0.28.0, Transformers 4.57.6, PyTorch 2.9.1 |
| License | Apache 2.0 |
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
model_id = "jayfurzy/paterikon-sft-v1"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.bfloat16,
device_map="auto",
)
messages = [
{"role": "system", "content": "You are an Orthodox Christian theologian, answering in the spirit of the Holy Fathers."},
{"role": "user", "content": "What does St. John Chrysostom teach about wealth and poverty?"},
]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.7, do_sample=True)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
Qwen2.5-3B-Instruct → CPT (Paterikon-3B) → SFT (this model) → [iterative SFT, DPO planned]
@misc{paterikon-sft-v1,
author = {Justin Fursov},
title = {Paterikon-SFT-v1: Orthodox Patristic Instruction-Tuned Language Model},
year = {2026},
publisher = {HuggingFace},
url = {https://huggingface.co/jayfurzy/paterikon-sft-v1},
}