Automatic Speech Recognition
Transformers
PyTorch
Basque
wav2vec2
audio
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use enterprise-explorers/wav2vec2-large-xlsr-53-eu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use enterprise-explorers/wav2vec2-large-xlsr-53-eu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="enterprise-explorers/wav2vec2-large-xlsr-53-eu")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("enterprise-explorers/wav2vec2-large-xlsr-53-eu") model = AutoModelForCTC.from_pretrained("enterprise-explorers/wav2vec2-large-xlsr-53-eu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from enterprise-explorers/wav2vec2-large-xlsr-53-eu: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/enterprise-explorers/wav2vec2-large-xlsr-53-eu/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://enterprise-explorers/wav2vec2-large-xlsr-53-eu/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/enterprise-explorers/wav2vec2-large-xlsr-53-eu/resolve/main/pytorch_model.bin
1.26 GB
- Xet hash:
- eeb0467b5e449c6bc920fcb2417f584833f1d7d96dbef29e4dd26be680408e59
- Size of remote file:
- 1.26 GB
- SHA256:
- adeb41e954f8f6c294919959482c15f0eef34fbbe1960c749ee3425153402d7a
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