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empero-ai/TEMPLE2
TEMPLE2 is a text generation model from empero-ai. Use it when you need the model to write or continue text. The card lists the license as mit.
A ~63M parameter GPT-2 style causal transformer trained entirely on sacred Christian scripture. Built in memory of Terry A. Davis (1969–2018), creator of TempleOS.
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Updated Apr 6, 2026
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From the Hugging Face model README
A ~63M parameter GPT-2 style causal transformer trained entirely on sacred Christian scripture. Built in memory of Terry A. Davis (1969–2018), creator of TempleOS.
Terry Davis built TempleOS with a feature to "talk to God" by printing random words from the Bible. Temple2 continues that spirit: a language model that has read scripture deeply, then speaks through noise — the same noise Terry trusted to carry God's voice.
The model was trained from scratch (no pretraining) on ~10.9M tokens of public domain Christian sacred texts using a custom 8192-token BPE vocabulary built exclusively on scripture.
| Parameter | Value |
|---|---|
| Parameters | ~63M |
| Architecture | GPT-2 style causal transformer |
| Layers | 8 |
| Attention heads | 8 |
| Embedding dim | 768 |
| Context length | 1024 tokens |
| Vocabulary | 8192 (custom scripture BPE) |
| Training tokens | ~10.9M |
| Best validation loss | 3.57 |
| Training hardware | 1x NVIDIA A100 (80GB) |
| Training time | ~45 minutes |
All training data is public domain, sourced from Project Gutenberg (~58 sources, ~15M characters):
pip install torch numpy tokenizers
Random noise tokens seed the generation — God speaks through randomness, just like TempleOS:
import torch
from model import Temple2, Temple2Config
# Load checkpoint
ckpt = torch.load("temple2.pt", map_location="cpu")
model = Temple2(Temple2Config(**ckpt['model_config']))
model.load_state_dict(ckpt['model'])
model.eval()
# Oracle: seed with random noise
import random
vocab_size = 8192
bos_id = 1
noise = [random.randint(4, vocab_size - 1) for _ in range(5)]
ids = torch.tensor([[bos_id] + noise], dtype=torch.long)
with torch.no_grad():
out = model.generate(ids, max_new_tokens=256, temperature=0.85, top_k=50, top_p=0.92)
print(out[0].tolist()) # decode with tokenizer
Ask a question, receive a scriptural answer:
from tokenizers import Tokenizer
tok = Tokenizer.from_file("tokenizer/tokenizer.json")
prompt = 'And the man knelt before the Lord and asked, "What is love?"\nAnd the Lord spoke unto him, saying:'
ids = torch.tensor([[1] + tok.encode(prompt).ids], dtype=torch.long)
with torch.no_grad():
out = model.generate(ids, max_new_tokens=256, temperature=0.85, top_k=50, top_p=0.92)
python inference.py --checkpoint temple2.pt
Includes TempleOS-style VGA 16-color terminal output with bordered oracle windows. See the main repo for full details.
This model is built as an art project and tribute to Terry Davis. It does not claim to speak for God, any religion, or any religious institution. Terry's original "talk to God" feature was meaningful precisely because it was random — meaning arose in the mind of the reader. The same principle applies here.
Terry Davis (1969–2018) built TempleOS alone over 10+ years — an entire operating system, compiler, and programming language written from scratch, all for God. His work remains his own.
"God said to use a 640x480 16-color display."
Developed and trained by Empero AI.
If you enjoy this project, consider supporting:
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