Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Italian
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use GIanlucaRub/whisper-tiny-it-9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GIanlucaRub/whisper-tiny-it-9 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="GIanlucaRub/whisper-tiny-it-9")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("GIanlucaRub/whisper-tiny-it-9") model = AutoModelForSpeechSeq2Seq.from_pretrained("GIanlucaRub/whisper-tiny-it-9") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Model description
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This model is the openai whisper small transformer adapted for Italian audio to text transcription.
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This model has weight decay set to 0.1 and the learning rate has been set to 1e-4 in the hyperparameter tuning process
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## Intended uses & limitations
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## Model description
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This model is the openai whisper small transformer adapted for Italian audio to text transcription.
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This model has weight decay set to 0.1 and the learning rate has been set to 1e-4 in the hyperparameter tuning process.
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## Intended uses & limitations
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