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:
- 3e9aed8fd0ef0f8d568cb04e599414a5bc8336747fe17ac45cca9fb73a0fd37c
- Size of remote file:
- 378 MB
- SHA256:
- bce26f2ee518d99b2f3c17de0498820baaf9573cf5b4eb3790a38308ed196361
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