Automatic Speech Recognition
Transformers
MLX
English
multilingual
whisper
speech-to-text
quantized
q8
apple-silicon
Instructions to use LibraxisAI/whisper-small-mlx-q8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LibraxisAI/whisper-small-mlx-q8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="LibraxisAI/whisper-small-mlx-q8")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("LibraxisAI/whisper-small-mlx-q8", dtype="auto") - MLX
How to use LibraxisAI/whisper-small-mlx-q8 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir whisper-small-mlx-q8 LibraxisAI/whisper-small-mlx-q8
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
Upload folder using huggingface_hub
Browse files- config.json +17 -0
- weights.safetensors +3 -0
config.json
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{
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"n_mels": 80,
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"n_audio_ctx": 1500,
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"n_audio_state": 768,
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"n_audio_head": 12,
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"n_audio_layer": 12,
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"n_vocab": 51865,
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"n_text_ctx": 448,
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"n_text_state": 768,
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"n_text_head": 12,
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"n_text_layer": 12,
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"quantization": {
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"group_size": 32,
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"bits": 8
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},
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"model_type": "whisper"
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}
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weights.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:dd8f199342c2d6880ec9cf4da6b68fdf17b427a687637351ba6b0c56844f4076
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size 272994304
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