Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Malay
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use Scrya/whisper-medium-ms with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Scrya/whisper-medium-ms with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Scrya/whisper-medium-ms")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Scrya/whisper-medium-ms") model = AutoModelForSpeechSeq2Seq.from_pretrained("Scrya/whisper-medium-ms") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb3d33300d1d2a069a77eee2921fb64cd65e654316f8c534f7f8d51777b129b9
- Size of remote file:
- 3.58 kB
- SHA256:
- 1d8ac2cf53f75e0e7d3c2aaca7e0966b9a26a1ef31f20c38027d20e7b278275a
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