Instructions to use TopSlayer/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TopSlayer/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="TopSlayer/model")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("TopSlayer/model") model = AutoModelForCTC.from_pretrained("TopSlayer/model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6e4d22064c86a9924e7dd60fd5448bbb906e6b1aa66bff8432a358db7af459ca
- Size of remote file:
- 1.26 GB
- SHA256:
- 454f53ff39ec0ea0c089f485bb2606caa3dfed465da8c03bed9e4f48a6a78c87
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