Instructions to use Benjaminpwh/sst-en_it_2_concat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Benjaminpwh/sst-en_it_2_concat with Transformers:
# Load model directly from transformers import AutoProcessor, Wav2Vec2_Qwen processor = AutoProcessor.from_pretrained("Benjaminpwh/sst-en_it_2_concat") model = Wav2Vec2_Qwen.from_pretrained("Benjaminpwh/sst-en_it_2_concat") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1116d7796ab03fae96556cde0792f9bfe608f511406523549043bd752fd63250
- Size of remote file:
- 11.4 MB
- SHA256:
- 6bafa2c0aa14c5fdc00a790fd0c98f067e8eb9078063ee18b5fe6794473ebb0a
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