Audio Classification
Transformers
Safetensors
audio-spectrogram-transformer
Generated from Trainer
Eval Results (legacy)
Instructions to use khizarAI/AST-finetuned-gtzan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use khizarAI/AST-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="khizarAI/AST-finetuned-gtzan")# pip install -U transformers accelerate # Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("khizarAI/AST-finetuned-gtzan") model = AutoModelForAudioClassification.from_pretrained("khizarAI/AST-finetuned-gtzan", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from khizarAI/AST-finetuned-gtzan: direct link, hf CLI and curl.
- Browser
- Download file 345 MB
-
https://huggingface.co/khizarAI/AST-finetuned-gtzan/resolve/main/model.safetensors
- Command line
-
hf download hf://khizarAI/AST-finetuned-gtzan/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/khizarAI/AST-finetuned-gtzan/resolve/main/model.safetensors
345 MB
- Xet hash:
- 3bc930414e4f1a6fbbff73bcc2482a6ec6ac01a3f8fd472e1a22b7c8f78e2bb3
- Size of remote file:
- 345 MB
- SHA256:
- 3deca8a290318de05eb821fed020106eeb6776fcaad5e757c9e80c2baaa61f25
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.