Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Indonesian
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use Scrya/whisper-medium-id-augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Scrya/whisper-medium-id-augmented with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Scrya/whisper-medium-id-augmented")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Scrya/whisper-medium-id-augmented") model = AutoModelForSpeechSeq2Seq.from_pretrained("Scrya/whisper-medium-id-augmented", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9410ac2ee7a382d52a8155b1cbd513415ca99f80ea9d175d7f91073997ff84f1
- Size of remote file:
- 3.06 GB
- SHA256:
- fc1fb8067d0e6d4e746d3c66daf2a05c4cb503fd93ea134c0cded37f11997e9c
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