Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Italian
whisper
Generated from Trainer
whisper-event
Eval Results (legacy)
Instructions to use luigisaetta/whisper-tiny-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use luigisaetta/whisper-tiny-it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="luigisaetta/whisper-tiny-it")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("luigisaetta/whisper-tiny-it") model = AutoModelForSpeechSeq2Seq.from_pretrained("luigisaetta/whisper-tiny-it", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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# whisper-tiny-it
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.3958
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- Wer: 0.2661
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# whisper-tiny-it
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the
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common_voice_11 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3958
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- Wer: 0.2661
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