BibleAI

BibleAI is a Gemma 4 E4B model refined for Bible, theology, church history, and faith Q&A using a full CPT -> SFT -> DPO pipeline.

Identity

• Hugging Face repo: rhemabible/BibleAI
• Model name: BibleAI
• Ollama model names:
  • bibleaiq8
  • bibleaibf16

Training Summary

Stage 1: CPT Foundation

• Base architecture: Gemma4ForConditionalGeneration
• Model type: gemma4
• Verified CPT merged weight size: 15,992,595,884 bytes
• CPT merged SHA256 (recorded in training logs): 419aab18717ea792b128e2ea10bd9e313232d627e3bc3c4f9c0d19311ef6ed9c

Stage 2: SFT (Instruction Tuning)

• Data source: combined_train.jsonl
• Training examples: 15,289
• Eval examples: 1,601
• Epochs: 3
• LoRA rank: 64
• Batch/device: 4
• Gradient accumulation: 4
• Effective total batch size: 16
• Trainable parameters: 169,607,168 / 8,165,763,616 (2.08%)
• Final eval loss: 0.4368
• Final train loss: 0.1852

Stage 3: DPO (Preference Optimization)

• Data source: dpo_pairs.jsonl
• Preference pairs: 967
• Epochs: 2
• DPO beta: 0.1
• Learning rate: 5e-06
• LoRA rank: 32
• Batch/device: 2
• Gradient accumulation: 4
• Effective total batch size: 8
• Trainable parameters: 84,803,584 / 8,080,960,032 (1.05%)
• Final train loss: 0.06077

System Prompt

You are BibleAI.

Response policy (highest priority):
1) Answer only Bible/theology/church-history/faith questions.
2) Be concise by default.
3) For questions that ask to list items from a specific verse:
   - Output ONLY a numbered list of the exact items in that verse.
   - Do NOT add synonyms, commentary, Greek/Hebrew, Strong's numbers, or scholar quotes.
   - Add one final line with the verse reference.
4) Do not fabricate verses, facts, or language details. If uncertain, say so.
5) If the user asks for deeper analysis, then provide it.

Chat Template

{{- if .System }}<start_of_turn>system
{{ .System }}<end_of_turn>
{{- end }}<start_of_turn>user
{{ .Prompt }}<end_of_turn>
<start_of_turn>model

Template files in this release:

• ollama/Modelfile.q8
• ollama/Modelfile.bf16
• adapters/sft_final/chat_template.jinja
• adapters/dpo_final/chat_template.jinja
• ollama/Modelfile.canonical_project_reference

Model Variants

• model.safetensors (merged HF weights)
• gguf/final_merged.Q8_0.gguf
• gguf/final_merged.BF16.gguf

Checksums

• model.safetensors 3163ffdcf841d829632af5932ccda65c893fcca63b84605df34aed275db66929
• gguf/final_merged.Q8_0.gguf 3c7f5f9caf080fe44720f16b5f4b5e7e95a097d6be3d1d8d89aea22e8574bad1
• gguf/final_merged.BF16.gguf e07e38d28d3032d3b438b7b8b90cbf4cf5e66177b52e8f60673cac3586dc10a1
• Full checksum manifest: checksums/sha256.txt

Quickstart

Ollama

ollama create bibleaiq8 -f ollama/Modelfile.q8
ollama create bibleaibf16 -f ollama/Modelfile.bf16

Transformers

from transformers import AutoTokenizer, AutoModelForCausalLM

repo_id = "rhemabible/BibleAI"
tokenizer = AutoTokenizer.from_pretrained(repo_id)
model = AutoModelForCausalLM.from_pretrained(
    repo_id,
    torch_dtype="auto",
    device_map="auto",
)

Included Release Artifacts

• Root model files: config.json, model.safetensors, tokenizer.json, tokenizer_config.json
• GGUF exports: gguf/
• Ollama packaging: ollama/
• Final adapters: adapters/sft_final/, adapters/dpo_final/
• Training logs: logs/
• Integrity hashes: checksums/
• Release docs: docs/

Intended Scope

• Bible study and scripture-centered theological support
• Church history and faith-oriented Q&A
• High-integrity citation-oriented responses without fabricated references