Automatic Speech Recognition
Transformers
PyTorch
JAX
Basque
wav2vec2
audio
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use cahya/wav2vec2-large-xlsr-basque with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cahya/wav2vec2-large-xlsr-basque with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="cahya/wav2vec2-large-xlsr-basque")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("cahya/wav2vec2-large-xlsr-basque") model = AutoModelForCTC.from_pretrained("cahya/wav2vec2-large-xlsr-basque", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 17a610319c5455317f1c8dd8bab10b193c5b2c826718152399ee2c949ce40ed4
- Size of remote file:
- 1.26 GB
- SHA256:
- c3cb9f5222d18d75ba17812a2016dba85c6e6fc226c06cc8cb2ef5a03f42ffff
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