Instructions to use siromii/tmp_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use siromii/tmp_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="siromii/tmp_trainer")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("siromii/tmp_trainer") model = AutoModelForAudioClassification.from_pretrained("siromii/tmp_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f0919bf95cb5a1c417449b090b3307d7c2426d3e985331f94af8d9bf1d27d2d
- Size of remote file:
- 5.78 kB
- SHA256:
- 954f48a2bc5338dcca76f211a6485d03ff036a641f0de17c128ddd03db30e11b
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