Upload the Distil-Whisper large-v3 conversion model to the Hugging Face hub

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
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+model.bin filter=lfs diff=lfs merge=lfs -text

README.md

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 ---
+language:
+  - en
+tags:
+  - audio
+  - automatic-speech-recognition
 license: mit
+library_name: ctranslate2
 ---
+
+# Whisper distil-large-v3 model for CTranslate2
+
+This repository contains the conversion of [distil-whisper/distil-large-v3](https://huggingface.co/distil-whisper/distil-large-v3) to the [CTranslate2](https://github.com/OpenNMT/CTranslate2) model format.
+
+This model can be used in CTranslate2 or projects based on CTranslate2 such as [faster-whisper](https://github.com/systran/faster-whisper).
+
+## Example
+
+```python
+from faster_whisper import WhisperModel
+
+model = WhisperModel("distil-large-v3")
+
+segments, info = model.transcribe("audio.mp3", language="en", condition_on_previous_text=False)
+for segment in segments:
+    print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
+```
+
+## Conversion details
+
+The original model was converted with the following command:
+
+```
+ct2-transformers-converter --model distil-whisper/distil-large-v3 --output_dir faster-distil-whisper-large-v3 \
+    --copy_files tokenizer.json preprocessor_config.json --quantization float16
+```
+
+Note that the model weights are saved in FP16. This type can be changed when the model is loaded using the [`compute_type` option in CTranslate2](https://opennmt.net/CTranslate2/quantization.html).
+
+## More information
+
+**For more information about the original model, see its [model card](https://huggingface.co/distil-whisper/distil-large-v3).**

config.json

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model.bin

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preprocessor_config.json

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+{
+  "chunk_length": 30,
+  "feature_extractor_type": "WhisperFeatureExtractor",
+  "feature_size": 128,
+  "hop_length": 160,
+  "n_fft": 400,
+  "n_samples": 480000,
+  "nb_max_frames": 3000,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "processor_class": "WhisperProcessor",
+  "return_attention_mask": false,
+  "sampling_rate": 16000
+}