Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Italian
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use ALM/whisper-it-medium-augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ALM/whisper-it-medium-augmented with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ALM/whisper-it-medium-augmented")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ALM/whisper-it-medium-augmented") model = AutoModelForSpeechSeq2Seq.from_pretrained("ALM/whisper-it-medium-augmented") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3bb88ba26f339db6921cf00c3343c1501eec9296fa528d7f06bf4af1dcc1a9f1
- Size of remote file:
- 3.58 kB
- SHA256:
- 035e3a0750c1920b485678fbe0879b9071a714907ac850ba87b8e4a88d790bf1
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