Update README.md
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README.md
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@@ -32,7 +32,7 @@ wget https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0-ggml/resolve/main/gg
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```bash
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wget https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-ggml/resolve/main/sample_ja_speech.wav
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make -j && ./main -m models/ggml-kotoba-whisper-v2.0.bin -f sample_ja_speech.wav --output-file transcription --output-json
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```
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Note that it runs only with 16-bit WAV files, so make sure to convert your input before running the tool. For example, you can use ffmpeg like this:
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Run inference on the sample audio:
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```bash
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make -j && ./main -m models/ggml-kotoba-whisper-v2.0-q5_0.bin -f sample_ja_speech.wav --output-file transcription.quantized --output-json
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```
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Note that the benchmark results are almost identical to the raw non-quantized model weight.
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```bash
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wget https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-ggml/resolve/main/sample_ja_speech.wav
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make -j && ./main -m models/ggml-kotoba-whisper-v2.0.bin -l ja -f sample_ja_speech.wav --output-file transcription --output-json
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```
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Note that it runs only with 16-bit WAV files, so make sure to convert your input before running the tool. For example, you can use ffmpeg like this:
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Run inference on the sample audio:
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```bash
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make -j && ./main -m models/ggml-kotoba-whisper-v2.0-q5_0.bin -l ja -f sample_ja_speech.wav --output-file transcription.quantized --output-json
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```
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Note that the benchmark results are almost identical to the raw non-quantized model weight.
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