Instructions to use fav-kky/wav2vec2-base-cs-de-100k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fav-kky/wav2vec2-base-cs-de-100k with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("fav-kky/wav2vec2-base-cs-de-100k") model = AutoModelForPreTraining.from_pretrained("fav-kky/wav2vec2-base-cs-de-100k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81b9f4c44a455b7d579756fcd9b30be8f21079cc3ac664308b650991942a36f0
- Size of remote file:
- 380 MB
- SHA256:
- 3de125412be701ff8c14827eb56eed8be4237659be826ef6273bce81c9bac5b8
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