Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use Scrya/whisper-medium-ms-augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Scrya/whisper-medium-ms-augmented with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Scrya/whisper-medium-ms-augmented")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Scrya/whisper-medium-ms-augmented") model = AutoModelForSpeechSeq2Seq.from_pretrained("Scrya/whisper-medium-ms-augmented", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba2c95ca9622ff872798d6e540c35e510207c21809231bfc148721aa0508f3c5
- Size of remote file:
- 3.06 GB
- SHA256:
- 8e08bd871f275f30e5cd42635e3e7e82aa3cc60c88af422fb05cc231784672d0
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