Audio Classification
Transformers
TensorBoard
Safetensors
hubert
Generated from Trainer
Eval Results (legacy)
Instructions to use vpingale07/distilhubert-v2-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vpingale07/distilhubert-v2-v4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="vpingale07/distilhubert-v2-v4")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("vpingale07/distilhubert-v2-v4") model = AutoModelForAudioClassification.from_pretrained("vpingale07/distilhubert-v2-v4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from vpingale07/distilhubert-v2-v4: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/vpingale07/distilhubert-v2-v4/resolve/main/training_args.bin
- Command line
-
hf download hf://vpingale07/distilhubert-v2-v4/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/vpingale07/distilhubert-v2-v4/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 63cd69e071ef79b29a4dc43d017eff34cae997312d9d3892e3bebead122afbaf
- Size of remote file:
- 4.92 kB
- SHA256:
- 085e47c46918989d247372d56a5caea49fece9a758328672b64a0353c4704887
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