Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Basque
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use xezpeleta/whisper-medium-eu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xezpeleta/whisper-medium-eu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="xezpeleta/whisper-medium-eu")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("xezpeleta/whisper-medium-eu") model = AutoModelForSpeechSeq2Seq.from_pretrained("xezpeleta/whisper-medium-eu") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0aeb8e638e2ac8df1c44a609d24c31d84998f458d81b36d10c69654686ef903b
- Size of remote file:
- 3.06 GB
- SHA256:
- b0c0a03f89a40ebf78d9625155537c70ab76c414e6b87f51a29bb2420fd68f50
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