Automatic Speech Recognition
Transformers
PyTorch
Armenian
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use arampacha/whisper-large-hy-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arampacha/whisper-large-hy-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="arampacha/whisper-large-hy-2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("arampacha/whisper-large-hy-2") model = AutoModelForSpeechSeq2Seq.from_pretrained("arampacha/whisper-large-hy-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa91a943766fe38450220e43d79721c5a8c87ffc86aef1f991c54682972caaed
- Size of remote file:
- 6.17 GB
- SHA256:
- b01c1cb55f90e6df4cc2c54ee864f1768b62a57607896ad809668915a46dc96d
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