Create README.md

README.md

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+---
+language: ja
+tags:
+  - audio
+  - automatic-speech-recognition
+license: apache-2.0
+---
+
+# Kotoba-Whisper: kotoba-whisper-v1.0 for Whisper cpp
+This repository contains the model weights for [kotoba-tech/kotoba-whisper-v1.0](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0)
+converted to [GGML](https://github.com/ggerganov/ggml) format. GGML is the weight format expected by C/C++ packages 
+such as [Whisper.cpp](https://github.com/ggerganov/whisper.cpp), for which we provide an example below.
+
+## Usage
+Kotoba-Whisper can be run with the [Whisper.cpp](https://github.com/ggerganov/whisper.cpp) package with the original 
+sequential long-form transcription algorithm.
+
+Steps for getting started:
+
+1. Clone the Whisper.cpp repository:
+```
+git clone https://github.com/ggerganov/whisper.cpp.git
+cd whisper.cpp
+```
+2. Install the Hugging Face Hub Python package:
+```bash
+pip install --upgrade huggingface_hub
+```
+And download the GGML weights for distil-large-v3 using the following Python snippet:
+
+```python
+from huggingface_hub import hf_hub_download
+
+hf_hub_download(repo_id='kotoba-tech/kotoba-whisper-v1.0-ggml', filename='ggml-kotoba-whisper-v1.0.bin', local_dir='./models')
+```
+
+Note that if you do not have a Python environment set-up, you can also download the weights directly with `wget`:
+
+```bash
+wget https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-ggml/resolve/main/ggml-kotoba-whisper-v1.0.bin -P ./models
+```
+
+3. Run inference using the provided sample audio:
+
+```bash
+make -j && ./main -m models/ggml-kotoba-whisper-v1.0.bin -f samples/jfk.wav
+```
+
+## Model Details
+
+For more information about the distil-large-v3 model, refer to the original [model card](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0).