Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Indonesian
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use Scrya/whisper-medium-id with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Scrya/whisper-medium-id with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Scrya/whisper-medium-id")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Scrya/whisper-medium-id") model = AutoModelForSpeechSeq2Seq.from_pretrained("Scrya/whisper-medium-id", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bf6abd4b7d6a8dcd97e1e45acf1f5a53915091697baad15edd58fc50acfde270
- Size of remote file:
- 3.06 GB
- SHA256:
- ad0c18415ba9d3c074047c84189fb01ed52aa3613ae4511cc7ce2cc267b1696a
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