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
Added requirements.txt
Browse files- requirements.txt +9 -0
requirements.txt
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torch>=1.7
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torchaudio
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transformers==4.26.0
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datasets>=2.7.1
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librosa
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jiwer
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evaluate>=0.3.0
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more-itertools
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tensorboard
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