Instructions to use Sammau/wav2vec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sammau/wav2vec2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sammau/wav2vec2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sammau/wav2vec2") model = AutoModelForCTC.from_pretrained("Sammau/wav2vec2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
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---
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datasets:
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- mozilla-foundation/common_voice_17_0
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language:
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- dv
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metrics:
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- wer
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base_model:
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- facebook/wav2vec2-large-xlsr-53
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pipeline_tag: automatic-speech-recognition
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library_name: transformers
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