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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3e738052a9d6a5a5e7ab083a3a37bb0070deb12edc54e58adceb73cae51f2aa1
- Size of remote file:
- 5.43 kB
- SHA256:
- d4d9992faa304c9ce937e5847e6e432e386e11a3edc5d5e9010155b4fc111f11
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