Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Italian
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use M2LabOrg/whisper-small-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use M2LabOrg/whisper-small-it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="M2LabOrg/whisper-small-it")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("M2LabOrg/whisper-small-it") model = AutoModelForSpeechSeq2Seq.from_pretrained("M2LabOrg/whisper-small-it") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d1102dd68d195109eefc147eb7e4bf759a53f8f34e76c568ffaf240e1e369fa
- Size of remote file:
- 967 MB
- SHA256:
- 3599be7a5f70b7e10489e62cc88965f9a162c3b602a8b002ae97d61769afe464
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