# Ai2 — How researchers adapted Dolma for better Thai language models

- Company: Ai2 (allenai.org)
- Announced: 2026-08-26
- Category: not stated
- Coverage: not counted
- Announcement: no
- Group: routine
- Source: https://allenai.org/blog/thai-llm-dolma
- Record: https://forck.live/items/18537-how-researchers-adapted-dolma-for-better-thai-language-models
- Subject: Olmo / Molmo / Asta

Ai2 reported that Thai researchers used its open Dolma toolkit to create Mangosteen, a 47-billion-token Thai pretraining corpus. The team modified Dolma's pipeline to handle Thai's sentence boundaries and quality filters, and found that their curation removed over 80% of Common Crawl data and nearly half of FineWeb2 while maintaining or improving model performance.

## Evidence

Verbatim from https://allenai.org/blog/thai-llm-dolma:

> A team of Thai researchers used Dolma as the foundation for a 47-billion-token Thai pretraining corpus, adapting the pipeline for Thai data, where existing approaches didn’t always account for the language’s unique characteristics.

---

Record: https://forck.live/items/18537-how-researchers-adapted-dolma-for-better-thai-language-models
Catalogue: https://forck.live/llms.txt
Current issue: https://forck.live/feed.md