Instructions to use mlx-community/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlx-community/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mlx-community/whisper-tiny")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mlx-community/whisper-tiny", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
75e2d0e
1
Parent(s): 4a34138
58b843e5f1523f29ac46e2b95a0199a5ccbd5a4d05f92894edf1b7ba4077aad1
Browse files- config.json +13 -0
- weights.npz +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": 384,
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"n_audio_head": 6,
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"n_audio_layer": 4,
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"n_vocab": 51865,
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"n_text_ctx": 448,
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"n_text_state": 384,
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"n_text_head": 6,
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"n_text_layer": 4,
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"model_type": "whisper"
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}
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weights.npz
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version https://git-lfs.github.com/spec/v1
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oid sha256:d5a3b8671ac7aab11a2c9d0f16e7da94bad5500d785856f438c6bd44c3723944
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size 74418182
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