Audio Classification
Transformers
Safetensors
audio-spectrogram-transformer
Generated from Trainer
Eval Results (legacy)
Instructions to use moonseok/AST_speechcommandsV2_final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moonseok/AST_speechcommandsV2_final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="moonseok/AST_speechcommandsV2_final")# pip install -U transformers accelerate # Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("moonseok/AST_speechcommandsV2_final") model = AutoModelForAudioClassification.from_pretrained("moonseok/AST_speechcommandsV2_final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from moonseok/AST_speechcommandsV2_final: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/moonseok/AST_speechcommandsV2_final/resolve/main/training_args.bin
- Command line
-
hf download hf://moonseok/AST_speechcommandsV2_final/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/moonseok/AST_speechcommandsV2_final/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- 03933f89a898e8b7e4b443cac0e8d682e302042a89f9e5f8f77f09ce85854b47
- Size of remote file:
- 4.6 kB
- SHA256:
- 76a7cc14c01efda2ebc9853a87a44d7fdc10944b53b7fff6b6935b1e10275a3b
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