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Update README.md

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@@ -62,6 +62,21 @@ Also, currently whisper.cpp and faster-whisper support the [sequential long-form
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  and only Huggingface pipeline supports the [chunked long-form decoding](https://huggingface.co/distil-whisper/distil-large-v3#chunked-long-form), which we empirically
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  found better than the sequnential long-form decoding.
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  ### Conversion details
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  The original model was converted with the following command:
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@@ -77,23 +92,12 @@ git clone https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0
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  # convert to ggml
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  python3 ./convert-h5-to-ggml.py ./kotoba-whisper-v1.0/ ../../whisper .
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  mv ggml-model.bin ggml-kotoba-whisper-v1.0
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- ```
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-
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- ### Quantized Model
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- To use the quantized model, download the quantized GGML weights:
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-
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- ```bash
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- wget https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-ggml/resolve/main/ggml-kotoba-whisper-v1.0-q5_0.bin -P ./models
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- ```
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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-v1.0-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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-
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-
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  ## Model Details
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  For more information about the kotoba-whisper-v1.0, refer to the original [model card](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0).
 
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  and only Huggingface pipeline supports the [chunked long-form decoding](https://huggingface.co/distil-whisper/distil-large-v3#chunked-long-form), which we empirically
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  found better than the sequnential long-form decoding.
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+
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+ ### Quantized Model
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+ To use the quantized model, download the quantized GGML weights:
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+
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+ ```bash
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+ wget https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-ggml/resolve/main/ggml-kotoba-whisper-v1.0-q5_0.bin -P ./models
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+ ```
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+
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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-v1.0-q5_0.bin -f sample_ja_speech.wav --output-file transcription.quantized --output-json
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+ ```
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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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+
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  ### Conversion details
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  The original model was converted with the following command:
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  # convert to ggml
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  python3 ./convert-h5-to-ggml.py ./kotoba-whisper-v1.0/ ../../whisper .
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  mv ggml-model.bin ggml-kotoba-whisper-v1.0
 
 
 
 
 
 
 
 
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+ # quantize ggml model
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+ cd ../
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+ ./quantize models/ggml-kotoba-whisper-v1.0.bin models/ggml-kotoba-whisper-v1.0-q5_0.bin q5_0
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  ```
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  ## Model Details
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  For more information about the kotoba-whisper-v1.0, refer to the original [model card](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0).