Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use amoghppatil/test_audio_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amoghppatil/test_audio_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="amoghppatil/test_audio_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("amoghppatil/test_audio_classification") model = AutoModelForAudioClassification.from_pretrained("amoghppatil/test_audio_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from amoghppatil/test_audio_classification: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/amoghppatil/test_audio_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://amoghppatil/test_audio_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/amoghppatil/test_audio_classification/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 0e10b255aa1986d675f38e0fdafd01848fe24439646e46e684f5debcac825f15
- Size of remote file:
- 4.92 kB
- SHA256:
- 30893d76063d0b9366ae22b51eb44d285a81df119ba493ed06eb3c5f35fc9b98
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