Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Italian
whisper
Generated from Trainer
whisper-event
Eval Results (legacy)
Instructions to use luigisaetta/whispermedium2plus-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use luigisaetta/whispermedium2plus-it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="luigisaetta/whispermedium2plus-it")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("luigisaetta/whispermedium2plus-it") model = AutoModelForSpeechSeq2Seq.from_pretrained("luigisaetta/whispermedium2plus-it") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5fea991f6a4df7af7652915e78a0e6cd63fc8fd7130340bf4065770a4ba86586
- Size of remote file:
- 1.53 GB
- SHA256:
- d6dfef13ff50628aecff15cae25a9a13e4f479b8c23f2e7d9a9a7a73cd166e97
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