Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Basque
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use deepdml/whisper-small-eu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepdml/whisper-small-eu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="deepdml/whisper-small-eu")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("deepdml/whisper-small-eu") model = AutoModelForSpeechSeq2Seq.from_pretrained("deepdml/whisper-small-eu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# openai/whisper-small
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_11_0 dataset.
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It achieves the following results on the evaluation set:
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# openai/whisper-small Basque-Euskera
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_11_0 dataset.
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It achieves the following results on the evaluation set:
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