Instructions to use Benjaminpwh/sst-en_de_13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Benjaminpwh/sst-en_de_13 with Transformers:
# Load model directly from transformers import AutoProcessor, DynamicWav2Vec2ForCTC processor = AutoProcessor.from_pretrained("Benjaminpwh/sst-en_de_13") model = DynamicWav2Vec2ForCTC.from_pretrained("Benjaminpwh/sst-en_de_13", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b4788716bf9a45624a0e8218764cd172ce4b05344798efbf43e5c336ee42366
- Size of remote file:
- 5.91 kB
- SHA256:
- 929a3e6b872f02db374a8443acf40105eea262734d4de8e2cb1a48c7db3d7c98
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