Audio Classification
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use JasHugF/whisper-tiny-zero-shot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JasHugF/whisper-tiny-zero-shot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="JasHugF/whisper-tiny-zero-shot")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("JasHugF/whisper-tiny-zero-shot") model = AutoModelForAudioClassification.from_pretrained("JasHugF/whisper-tiny-zero-shot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb8ed99a9e46fe577292b7ae65523d33bad34bee394be03beeff7a92175cfb71
- Size of remote file:
- 5.3 kB
- SHA256:
- ec8cccb24b8cfdb72ec013a933e1ccccf9b47af649b4cba693fa4341f0d0e97e
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