OpenVerifiableLLM 23M
A 23.1M-parameter GPT trained on exactly one pass over all of English Wikipedia (the 2026-09-01 dump), then a short conversation phase. Its training can be recomputed bit for bit: all 37 training segments were recomputed on a second RTX 5090 and matched. The model is small and often wrong about facts. The point is that you can check how it was made.
- Code and docs: https://github.com/AOSSIE-Org/OpenVerifiableLLM
- Training data and the training record (chain, checkpoints, timestamped anchor):
AOSSIE/openverifiable-enwiki-20260901-20260918-r1-evidence - How it works: https://github.com/AOSSIE-Org/OpenVerifiableLLM/blob/main/docs/how-it-works.md
Files
| File | What it is |
|---|---|
conversation.safetensors |
The chat model (chain entry 37) |
base.safetensors |
The Wikipedia-only model, before the conversation phase (chain entry 31) |
ovl-23m-chat-F32.gguf |
The chat model for llama.cpp and Ollama, all weights F32 |
Modelfile |
The Ollama build file, with the training chat format |
recipe.json |
The training recipe: model size, schedule, seed |
tokenizer.json |
The byte-level BPE tokenizer (31,995 tokens after 5 control tokens) |
SHA-256 of each file (check a download with sha256sum -c):
00c1c450acb2619f616af973d283fe5ef5cf1baaae5f16ff80bca97688f25168 conversation.safetensors
5404ce5c7583e2e299d6e9fa44ed48e98bc5b5e11bc976905e8466a6fc5c36c2 base.safetensors
541d49c97b87cd4ed0acb90b4327535ee20b8c11c452e2583d460154e9d980de ovl-23m-chat-F32.gguf
30631c28d3c5ce44a2ff4cdd5c74c415dad12f40df87a0b118d0ffa1c4d4b5b8 Modelfile
28a2fb407a5582ae95c9e9b0bba2c14df946e87bba037800399c6059256b6e6d recipe.json
6eab0d9bcd5736cee484992b24e7a84459bee1cc3024c0e958a76842a57728c0 tokenizer.json
The GGUF has the same bytes as ovl-23m-chat.gguf in the GitHub releases.
The safetensors files hold exactly the weights of the released .pt files, including both copies of
the tied embedding and output weights. The metadata key ovl records the .pt file's SHA-256 and the
model digest. simple/export_safetensors.py rebuilds these files byte for byte from the .pt files.
Use it
ollama run ryoari/openverifiablellm "Tell me about the Moon."
The chat format is <|user|> question <|eos|> <|assistant|> answer <|eos|>. llama.cpp's outputs
are close to PyTorch's but not bit-identical, so use the safetensors files to check the model.
| Architecture | GPT-2-style: 6 layers, 6 heads, 384 dimensions, 512-token context, tied embeddings |
| Training | 560,177 Wikipedia updates and 441 conversation updates, batch 32 × 512 tokens, seed 1234 |
| Data | 7,232,582 Wikipedia articles (7,118,121,139 training targets) and 3,481 OpenAssistant conversations |
Check it
On a laptop, check that a weights file is exactly the state in the timestamped training record. This
needs ovl.py from v1.1.0 or newer, Python 3.12 or newer, git, openssl and network access:
pip install huggingface_hub torch numpy safetensors
hf download AOSSIE/OpenVerifiableLLM-23M conversation.safetensors --local-dir model
hf download AOSSIE/openverifiable-enwiki-20260901-20260918-r1-evidence --repo-type dataset \
--include "release/simple-run/*" --exclude "*/ckpt-*" --exclude "*.pt" --local-dir ovl
git clone -q --depth 1 --branch v1.1.0 https://github.com/AOSSIE-Org/OpenVerifiableLLM ovl-code
OVL_DEVICE=cpu python ovl-code/simple/ovl.py verify --run ovl/release/simple-run --weights model/conversation.safetensors
# anchor ...: chain head MATCH (38 entries)
# anchor timestamp freetsa: OK (Oct 20 14:38:43 2026 GMT)
# anchor timestamp digicert: OK (Oct 20 14:38:43 2026 GMT)
# weights model/conversation.safetensors: MATCH chain entry 37
This is a consistency check: it recomputes no training. To verify the training itself, recompute a segment on an RTX 5090 (about an hour, about US$1.50): https://github.com/AOSSIE-Org/OpenVerifiableLLM/blob/main/docs/verify.md.
Limits
- The model is small. It writes fluent, encyclopedia-style text, often gets facts wrong, and holds a basic conversation. "Verified" is about how it was made, not about what it says.
- Bits match only on the training GPU type (RTX 5090). An RTX 4090, an H100 and a CPU give different bits.
- So far every segment check was run by the project. No independent third party has checked one yet.
- The timestamps prove that the record existed by 2026-10-20 14:38:43 UTC, not when or how training happened.
License
GPL-3.0, like the code. The training data keeps its own terms: English Wikipedia text (generally
CC BY-SA 4.0, with documented exceptions) and OpenAssistant oasst1 (Apache 2.0). See the dataset's
LICENSES.md.
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