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README.md
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@@ -3,7 +3,6 @@ license: apache-2.0
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language:
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- th
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base_model: biodatlab/whisper-th-large-combined
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library_name: transformers
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tags:
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- whisper
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- Pytorch
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whisper-th-large-ct2 is the CTranslate2 format of [biodatlab/whisper-th-large-combined](https://huggingface.co/biodatlab/whisper-th-large-combined), comparable with [WhisperX](https://github.com/m-bain/whisperX) and [faster-whisper](https://github.com/SYSTRAN/faster-whisper), which enables:
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- 🤏 **Half the size** of
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- ⚡️ Batched inference for **70x** real-time transcription using Whisper large-v2.
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- 🪶 A faster-whisper backend, requiring **<8GB GPU memory** for large-v2 with beam_size=5.
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- 🎯 Accurate word-level timestamps using wav2vec2 alignment.
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language:
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- th
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base_model: biodatlab/whisper-th-large-combined
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tags:
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- whisper
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- Pytorch
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whisper-th-large-ct2 is the CTranslate2 format of [biodatlab/whisper-th-large-combined](https://huggingface.co/biodatlab/whisper-th-large-combined), comparable with [WhisperX](https://github.com/m-bain/whisperX) and [faster-whisper](https://github.com/SYSTRAN/faster-whisper), which enables:
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- 🤏 **Half the size** of original Huggingface format.
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- ⚡️ Batched inference for **70x** real-time transcription using Whisper large-v2.
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| 17 |
- 🪶 A faster-whisper backend, requiring **<8GB GPU memory** for large-v2 with beam_size=5.
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| 18 |
- 🎯 Accurate word-level timestamps using wav2vec2 alignment.
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