Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Italian
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use GIanlucaRub/whisper-tiny-it-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GIanlucaRub/whisper-tiny-it-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="GIanlucaRub/whisper-tiny-it-1")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("GIanlucaRub/whisper-tiny-it-1") model = AutoModelForSpeechSeq2Seq.from_pretrained("GIanlucaRub/whisper-tiny-it-1") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): ccd6492
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README.md
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- name: Whisper Tiny It - Gianluca Ruberto
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results:
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name: Automatic Speech Recognition
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# Whisper Tiny It - Gianluca Ruberto
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
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It achieves the following results on the evaluation set:
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metrics:
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- wer
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model-index:
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- name: Whisper Tiny It 1- Gianluca Ruberto
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results:
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- task:
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name: Automatic Speech Recognition
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---
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# Whisper Tiny It 1 - Gianluca Ruberto
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
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It achieves the following results on the evaluation set:
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