Instructions to use NbAiLab/wav2vec2-xlsr-300m-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/wav2vec2-xlsr-300m-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/wav2vec2-xlsr-300m-test")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("NbAiLab/wav2vec2-xlsr-300m-test") model = AutoModelForCTC.from_pretrained("NbAiLab/wav2vec2-xlsr-300m-test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45df9dbaadaa9fdf523b6f1b98bf6c59b42ec488a15c5184eed73d793f64e4ab
- Size of remote file:
- 1.26 GB
- SHA256:
- e964d13779b9a8c1e559a0f2c6b74dffb3852e5c214ad05effb50eff22848334
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