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:
- 41b515b8260aa626fcd840e55324acc2873803d483e5c9b9af1f53b02d11d10d
- Size of remote file:
- 3.06 GB
- SHA256:
- a6b42d7a666d3a148908a327b24d37beef1d82a8962558b66ce5bb20f48f15c0
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