Add weights and readme

README.md

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+---
+language:
+  - en
+tags:
+  - audio
+  - automatic-speech-recognition
+license: mit
+---
+
+# Distil-Whisper: distil-large-v3 for Whisper cpp
+
+This repository contains the model weights for [distil-large-v3](https://huggingface.co/distil-whisper/distil-large-v3)
+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.
+
+Compared to previous Distil-Whisper releases, the distil-large-v3 is specifically designed to give one-to-one equivalence
+with the Whisper cpp long-form transcription algorithm. In our benchmark over 4 out-of-distribution datasets, distil-large-v3
+outperformed distil-large-v2 by 5% WER average. Thus, you can expect significant performance gains by switching to this 
+latest checkpoint.
+
+## Usage
+
+Distil-Whisper can be run with the [Whisper.cpp](https://github.com/ggerganov/whisper.cpp) package with the original 
+sequential long-form transcription algorithm. In a provisional benchmark on Mac M1, distil-large-v3 is over 5x faster 
+than Whisper large-v3, while performing to within 0.8% WER over long-form audio.
+
+Steps for getting started:
+
+1. Clone the Whisper.cpp repository:
+```
+git clone https://github.com/ggerganov/whisper.cpp.git
+cd whisper.cpp
+```
+2. Download the GGML weights for distil-large-v3 in fp16 from the Hugging Face Hub:
+
+```bash
+python -c "from huggingface_hub import hf_hub_download; hf_hub_download(repo_id='distil-whisper/distil-large-v3-ggml', filename='ggml-distil-large-v3.bin', local_dir='./models')"
+```
+
+Note that if you do not have the `huggingface_hub` package installed, you can also download the weights with `wget`:
+
+```bash
+wget https://huggingface.co/distil-whisper/distil-large-v3-ggml/resolve/main/ggml-distil-large-v3.bin -P ./models
+```
+
+3. Run inference using the provided sample audio:
+
+```bash
+make -j && ./main -m models/ggml-distil-large-v3.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/distil-whisper/distil-large-v3).
+
+## License
+
+Distil-Whisper inherits the [MIT license](https://github.com/huggingface/distil-whisper/blob/main/LICENSE) from OpenAI's Whisper model.
+
+## Citation
+
+If you use this model, please consider citing the [Distil-Whisper paper](https://arxiv.org/abs/2311.00430):
+```
+@misc{gandhi2023distilwhisper,
+      title={Distil-Whisper: Robust Knowledge Distillation via Large-Scale Pseudo Labelling}, 
+      author={Sanchit Gandhi and Patrick von Platen and Alexander M. Rush},
+      year={2023},
+      eprint={2311.00430},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+

ggml-distil-large-v3.bin

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ggml-distil-large-v3.fp32.bin

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