Duplicate from mobiuslabsgmbh/faster-whisper-large-v3-turbo

Co-authored-by: Jilt Sebastian <[email protected]>

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README.md

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+---
+license: mit
+---
+
+# Whisper large-v3 turbo model for CTranslate2
+
+This repository contains the conversion of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) to the [CTranslate2](https://github.com/OpenNMT/CTranslate2) model format.
+
+This model can be used in CTranslate2 or projects based on CTranslate2 models such as [faster-whisper](https://github.com/systran/faster-whisper). It is called automatically for [Mobius Labs fork of faster-whisper](https://github.com/mobiusml/faster-whisper).
+
+## Example
+
+
+```python
+from faster_whisper import WhisperModel
+
+model = WhisperModel("faster-whisper-large-v3-turbo")
+
+segments, info = model.transcribe("audio.mp3")
+for segment in segments:
+    print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
+```
+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).
+
+
+## Conversion details
+The openAI model was converted with the following command:
+```
+ct2-transformers-converter --model openai/whisper-large-v3-turbo --output_dir faster-whisper-large-v3-turbo \
+    --copy_files tokenizer.json preprocessor_config.json --quantization float16
+```
+
+### More Information
+
+For more information about the original model, see its [model card](https://huggingface.co/openai/whisper-large-v3-turbo).

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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
+}