Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use sgangireddy/whisper-largev2-mls-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgangireddy/whisper-largev2-mls-it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sgangireddy/whisper-largev2-mls-it")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("sgangireddy/whisper-largev2-mls-it") model = AutoModelForSpeechSeq2Seq.from_pretrained("sgangireddy/whisper-largev2-mls-it") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4985df4c6e4717c350da5e189cac02c895f684090a8d5aefb2ae13e8ca329bf
- Size of remote file:
- 6.17 GB
- SHA256:
- 0eda7c2098f5a034dafe581ffe6ff0f2ff8a71e0e8a58125585d81c21bba8218
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