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:
- c8370669d3a83b5ef198d5a8500aaad24228a7b9d03e8c9b96a494821e6091d3
- Size of remote file:
- 4.73 kB
- SHA256:
- c4d311ec7d5167eb4db1105f1cb58ff2c22e5b8dc152ea69471b918f77bbe843
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