Instructions to use snolyai/resultsfinal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use snolyai/resultsfinal with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="snolyai/resultsfinal")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("snolyai/resultsfinal") model = AutoModelForAudioClassification.from_pretrained("snolyai/resultsfinal", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 807c0865d9eb72b1e2c87c665bee8887ecf056eba7f084220574f07c4fcc4d9f
- Size of remote file:
- 1.26 GB
- SHA256:
- 8bf76a01783dabb2880727afc44909447dc0a639d640946d4076f87aa234eac9
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