Automatic Speech Recognition
Transformers
PyTorch
Basque
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use zuazo/whisper-large-eu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zuazo/whisper-large-eu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="zuazo/whisper-large-eu")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("zuazo/whisper-large-eu") model = AutoModelForSpeechSeq2Seq.from_pretrained("zuazo/whisper-large-eu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 829953857223be5c7a0a6d8618c2d7830363a17d68f2474a8adc9ccdb189a70d
- Size of remote file:
- 6.17 GB
- SHA256:
- 2f3996063c0827eecf60c5eb3dab356c6b2b462a098e426d216090bb226cbcf8
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