Instructions to use GENG/wav2vec2.0_lv60_timi_pr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GENG/wav2vec2.0_lv60_timi_pr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="GENG/wav2vec2.0_lv60_timi_pr")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("GENG/wav2vec2.0_lv60_timi_pr") model = AutoModelForCTC.from_pretrained("GENG/wav2vec2.0_lv60_timi_pr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a63554fdcf425ba94a072fdc74d4d3deade717b943dd25780b67401639d76bf
- Size of remote file:
- 1.26 GB
- SHA256:
- 70a622484fde1190a64a5198341909689c6639d1fe5898638662e7276e94a344
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