Audio Classification
Transformers
PyTorch
Safetensors
English
wav2vec2
audio
musical-instruments
Eval Results (legacy)
Instructions to use Bhaveen/Musical-Instrument-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bhaveen/Musical-Instrument-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Bhaveen/Musical-Instrument-Classification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Bhaveen/Musical-Instrument-Classification") model = AutoModelForAudioClassification.from_pretrained("Bhaveen/Musical-Instrument-Classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 485c99a5bd1eb5bfb99230881c52fb40c8cbe8c53b1442db0cc344ec656d86ab
- Size of remote file:
- 4.02 kB
- SHA256:
- fe4bc8d51167f68712e533a940025e3b1448d389451dcbbef874afb56f62835b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.