olifant-speculative-ibases

Olifant instance bases for speculative decoding (INLG 2026)

Four trained TiMBL IGTree instance bases used as speculative-decoding draft models in:

Antal van den Bosch. 2026. Towards Green Text Generation: Memory-Based Speculative Decoding. In Proceedings of the International Natural Language Generation Conference (INLG 2026). To appear.

Code: https://github.com/antalvdb/olifant-speculative

All models: IGTree (-a1), context window 4, tokenized with mistralai/Mistral-7B-v0.1 SentencePiece, no class distributions (+D off). Each directory holds the .ibase, its .wgt weights file, and an olifant_config.json recording tokenizer, window size, and algorithm.

Usage: download a directory into the models/ folder of the olifant-speculative repo and pass it to the benchmark runners. Loading is done by timblserver (one-time, up to ~1 minute for the largest ibase); queries then take well under a millisecond on CPU.

Training corpora are used under their respective terms (FineWeb-Edu ODC-By, WikiText CC BY-SA, PubMed and LexGLUE per their distributions). The instance bases store 4-token context windows with next-token labels derived from these corpora.