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README.md
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Trained on **1,022.78 hours (594,231 clips)** of curated Thai speech using quantization-aware LoRA (`CQ W4 STE + A8`) and an expanded Thai SentencePiece vocabulary, the final model compiles into a standalone **32.49 MB** `.cact` archive ready for fast on-device CPU/GPU/mobile inference.
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## Model Summary
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Trained on **1,022.78 hours (594,231 clips)** of curated Thai speech using quantization-aware LoRA (`CQ W4 STE + A8`) and an expanded Thai SentencePiece vocabulary, the final model compiles into a standalone **32.49 MB** `.cact` archive ready for fast on-device CPU/GPU/mobile inference.
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- **GitHub**: [https://github.com/wannaphong/MaprangSTT](https://github.com/wannaphong/MaprangSTT)
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- **In-Browser Web Demo (`cactus-needle`)**: [https://wannaphong.github.io/MaprangSTT/demo](https://wannaphong.github.io/MaprangSTT/demo)
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## Model Summary
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