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README.md
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---
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license: mit
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language:
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- en
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- pl
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- de
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- fr
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- es
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- it
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- pt
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- nl
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- ru
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- zh
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- ja
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- ko
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- ar
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- hi
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- multilingual
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tags:
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- whisper
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- speech-to-text
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- mlx
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- quantized
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- q8
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- apple-silicon
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library_name: transformers
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pipeline_tag: automatic-speech-recognition
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base_model: openai/whisper-large-v3
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---
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# Whisper Large V3 - MLX Q8 Quantized
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8-bit quantized version of OpenAI's Whisper Large V3, optimized for Apple Silicon with MLX.
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## Model Details
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| Property | Value |
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|----------|-------|
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| Original Model | [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) |
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| Parameters | ~1.55B |
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| Quantization | INT8 (Q8) |
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| Size | ~1.6GB |
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| Decoder Layers | 32 |
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Best accuracy among Whisper models. Use `large-v3-turbo` for faster inference with slightly lower accuracy.
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## Other Whisper Models
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| Model | Size | Speed | Link |
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|-------|------|-------|------|
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| small | ~300MB | Fastest | [LibraxisAI/whisper-small-mlx-q8](https://huggingface.co/LibraxisAI/whisper-small-mlx-q8) |
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| medium | ~800MB | Fast | [LibraxisAI/whisper-medium-mlx-q8](https://huggingface.co/LibraxisAI/whisper-medium-mlx-q8) |
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| **large-v3** (this) | ~1.6GB | Slow | - |
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| large-v3 q4 | ~900MB | Medium | [LibraxisAI/whisper-large-v3-q4](https://huggingface.co/LibraxisAI/whisper-large-v3-q4) |
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| large-v3-turbo | ~900MB | Fast | [LibraxisAI/whisper-large-v3-turbo-mlx-q8](https://huggingface.co/LibraxisAI/whisper-large-v3-turbo-mlx-q8) |
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## Usage
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```python
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import mlx_whisper
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result = mlx_whisper.transcribe(
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"audio.wav",
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path_or_hf_repo="LibraxisAI/whisper-large-v3-mlx-q8"
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)
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print(result["text"])
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```
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## Supported Languages
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Full multilingual support: English, Polish, German, French, Spanish, Italian, Portuguese, Dutch, Russian, Chinese, Japanese, Korean, Arabic, Hindi, and 90+ additional languages.
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## Hardware Requirements
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- Apple Silicon Mac (M1/M2/M3/M4)
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- Minimum 16GB RAM recommended
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## License
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MIT - inherited from OpenAI Whisper.
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---
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*Converted by [LibraxisAI](https://huggingface.co/LibraxisAI) using mlx-whisper*
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