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:
- 88c404b9aac627153421f2874f866f26db68afe0b641a1957f49ccd3eb79679d
- Size of remote file:
- 3.58 kB
- SHA256:
- eea417c01ae741fc710dbd876030b68ed7a0995e9d4077514d5ed566a5faf4b4
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