Instructions to use dragonSwing/viwav2vec2-base-100h with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dragonSwing/viwav2vec2-base-100h with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="dragonSwing/viwav2vec2-base-100h")# Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("dragonSwing/viwav2vec2-base-100h") model = AutoModelForPreTraining.from_pretrained("dragonSwing/viwav2vec2-base-100h") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9590096b0c61591e14289597af8b53778e23da2c6bb876372f27616ea705638f
- Size of remote file:
- 380 MB
- SHA256:
- 249ccbc8d972e557c129ff9f403fb94fc3f688a2050e0c67adbba9dccf98cce3
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