Instructions to use MuhammadaliML/playground_models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MuhammadaliML/playground_models with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="MuhammadaliML/playground_models")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("MuhammadaliML/playground_models") model = AutoModelForAudioClassification.from_pretrained("MuhammadaliML/playground_models") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8344304a3862d4fdcda6a5956f8ba6fb9f54f264dfcb71769734c8273ff2d9ae
- Size of remote file:
- 4.66 kB
- SHA256:
- e8ce2779e7561055c4324b6f10d8cac3662edfb11c3d7055f14c178bac95ae41
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