Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Malayalam
whisper
whisper-event
common-voice
Instructions to use apzl/whisper-small-ml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apzl/whisper-small-ml with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="apzl/whisper-small-ml")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("apzl/whisper-small-ml") model = AutoModelForSpeechSeq2Seq.from_pretrained("apzl/whisper-small-ml") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e28e9743dd01e7aa66e7442cb6d7cb53f7bb637e46a589776ad7e8af00cd5efc
- Size of remote file:
- 3.58 kB
- SHA256:
- f4c4524f51c8a01ba1d310b1ce066db45126030b234a92ea9c3d5730bdcc0183
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