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Thai researchers create Mangosteen dataset for LLMs using Dolma toolkit

By PulseAugur Editorial · [1 sources] ·

A Thai research team has developed a new dataset called Mangosteen, comprising 47 billion tokens, specifically for training Thai large language models (LLMs). They utilized the Dolma data-curation toolkit, originally developed by the Allen Institute for Artificial Intelligence, to filter existing web datasets. This process resulted in a more focused corpus that enhanced the performance of Thai LLMs, even with a reduced amount of data compared to broader datasets. AI

IMPACT This development could lead to more capable and specialized Thai language models, improving AI performance for the region.

RANK_REASON Research team develops a new dataset for LLMs using an existing toolkit. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Bluesky Jetstream — AI desk →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Thai researchers create Mangosteen dataset for LLMs using Dolma toolkit

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21 / 100
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Tool
Research team develops a new dataset for LLMs using an existing toolkit. [lever_c_demoted from research: ic=1 ai=1.0]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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model release, infra
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. Bluesky Jetstream — AI desk TIER_1 English(EN) · ai2.bsky.social ·

    A Thai research team adapted our Dolma data-curation toolkit to build Mangosteen, a 47B-token corpus for Thai LLMs.

    A Thai research team adapted our Dolma data-curation toolkit to build Mangosteen, a 47B-token corpus for Thai LLMs. They used Dolma to filter widely used web datasets into a smaller corpus that improved Thai LLM performance despite using less data. 🧵 buff.ly/fvLSIru

    LINKS allenai.org/…/thai-llm-dolma

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