Instructions to use mazesmazes/tiny-audio-next with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mazesmazes/tiny-audio-next with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="mazesmazes/tiny-audio-next", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mazesmazes/tiny-audio-next", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e9416eceabe93dce96f462ace66465cddd91eb2d6fd994ba019b3d531f80816c
- Size of remote file:
- 2.41 GB
- SHA256:
- 1ae48e8cbe028404824d5bcb782d4bb1641f43648cd86f5fa4937ce5682762e4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.