Automatic Speech Recognition
Transformers
PyTorch
Malayalam
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use parambharat/whisper-tiny-ml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use parambharat/whisper-tiny-ml with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="parambharat/whisper-tiny-ml")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("parambharat/whisper-tiny-ml") model = AutoModelForSpeechSeq2Seq.from_pretrained("parambharat/whisper-tiny-ml") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60f1b32f32251dcf59df04afdb23d4bd14839a7d0aa986fee8769ab63abdf2de
- Size of remote file:
- 151 MB
- SHA256:
- ca7758081860de3e38bb45f8e8f28163506d9155e20dcf43bf940da377acde98
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