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--- |
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license: apache-2.0 |
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datasets: |
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- techiaith/banc-trawsgrifiadau-bangor |
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- techiaith/commonvoice_18_0_cy |
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language: |
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- cy |
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base_model: |
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- openai/whisper-base |
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pipeline_tag: automatic-speech-recognition |
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tags: |
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- whispercpp |
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--- |
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# whisper-base-ft-btb-cv-cy-cpp |
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This model is a version of the [openai/whisper-base](https://huggingface.co/openai/whisper-base) model, fine-tuned with |
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transcriptions of Welsh language spontaneous speech from Banc Trawsgrifiadau Bangor (btb) dataset, as well as read |
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speech from Welsh Common Voice version 18 (cv) for additional training, and then |
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[converted for use in whisper.cpp](https://github.com/ggerganov/whisper.cpp/tree/master/models#fine-tuned-models). |
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Whispercpp is a C/C++ port of Whisper that provides high performance inference on hardware such as desktops, laptops |
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and mobile devices, thus giving an offline option. |
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The model is a smaller in size to the corresponding model for hosting on cloud GPU based infrastructure |
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[techiaith/whisper-large-v3-ft-btb-cv-cy](https://huggingface.co/techiaith/whisper-large-v3-ft-btb-cv-cy) and thus |
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not as accurate. |
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It achieves the following WER results for transcribing Welsh language spontaneous speech: |
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- WER: 62.76 |
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- CER: 27.70 |
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## Usage |
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whispercpp makes it easy to use models in many platforms and applications. See the 'examples' folder |
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in the whispercpp github repo for more information and example code. |
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To get quickly started with whispercpp's basic usage however, follow the '[Quick Start](https://github.com/ggerganov/whisper.cpp?tab=readme-ov-file#quick-start)' |
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but download this model with the following command: |
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`$ wget https://huggingface.co/techiaith/whisper-base-ft-btb-cv-cy-cpp/resolve/main/ggml-model.bin` |
