Instructions to use codingaslu/logs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codingaslu/logs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="codingaslu/logs")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("codingaslu/logs") model = AutoModelForAudioClassification.from_pretrained("codingaslu/logs") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f338a75a7a928cd25c19ef61c55fd339e94883933c023663c197bd360740a1ca
- Size of remote file:
- 1.26 GB
- SHA256:
- 417a1850228634ec15a3c59f614acc20768b9f123abff15c7e3005bed1f15da5
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