Instructions to use Lakoc/fisher_conformer_enc_14_layers_smaller_hidden with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lakoc/fisher_conformer_enc_14_layers_smaller_hidden with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Lakoc/fisher_conformer_enc_14_layers_smaller_hidden")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Lakoc/fisher_conformer_enc_14_layers_smaller_hidden") model = AutoModel.from_pretrained("Lakoc/fisher_conformer_enc_14_layers_smaller_hidden", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6194e3a1ad96359e9f4fedad84c01395d9ee9cef62fbd965cc3f130d889540f2
- Size of remote file:
- 151 MB
- SHA256:
- 09e8b2edd82da293a9d73e2f22ba4a43ef0d25176179854105591296b33769ec
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