Audio Classification
Transformers
PyTorch
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use pratap18/audio_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pratap18/audio_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="pratap18/audio_classification_model")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("pratap18/audio_classification_model") model = AutoModelForAudioClassification.from_pretrained("pratap18/audio_classification_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitignore from pratap18/audio_classification_model: direct link, hf CLI and curl.
- Browser
- Download file 13 Bytes
-
https://huggingface.co/pratap18/audio_classification_model/resolve/main/.gitignore
- Command line
-
hf download hf://pratap18/audio_classification_model/.gitignore
-
curl -L -o .gitignore https://huggingface.co/pratap18/audio_classification_model/resolve/main/.gitignore
13 Bytes
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