1.2 KiB
1.2 KiB
BuddhaGPT
Fine-tune + RAG experiment: a small local model trained and grounded on the Pali Canon (via SuttaCentral's Bilara texts).
Data generation
Synthetic instruction pairs (data/instructions.jsonl) are generated from corpus/suttas.jsonl
via scripts/gen_data.py, using OpenRouter model ~deepseek/deepseek-v4-flash-latest (the
tilde prefix is part of OpenRouter's real catalog ID for this "latest" alias — verified against
the live /api/v1/models catalog, not a typo).
Token usage / cost:
- Original full run (
--mode full, 3,200 calls, variants 0–1 only): totals were not persisted and the generating process died before a report was written, so these figures are an estimate, not measured:5.2M input / 1.8M output tokens, ≈$0.4–0.7 at list pricing ($0.08/M in, $0.16/M out). - Template top-up run (
--mode topup, 2,300 calls, variants 2–5, 0 failures): measured — 1,994,673 input tokens / 1,618,867 output tokens, $0.42 at list pricing (~$0.08/M in, $0.16/M out). See.superpowers/sdd/2026-08-14-buddha-gpt/task-5-report.mdfor the full fix-round report, including per-template pair counts.