Instructions to use LeeTung/WhisperClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LeeTung/WhisperClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="LeeTung/WhisperClassification")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("LeeTung/WhisperClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: mit | |
| pipeline_tag: audio-classification | |
| tags: | |
| - model_hub_mixin | |
| - pytorch_model_hub_mixin | |
| This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: | |
| - Library: https://huggingface.co/LeeTung/WhisperClassification | |
| - Docs: [More Information Needed] |