Instructions to use semaj83/distilhubert-finetuned-gtzan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use semaj83/distilhubert-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="semaj83/distilhubert-finetuned-gtzan")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("semaj83/distilhubert-finetuned-gtzan") model = AutoModelForAudioClassification.from_pretrained("semaj83/distilhubert-finetuned-gtzan", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from semaj83/distilhubert-finetuned-gtzan: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/semaj83/distilhubert-finetuned-gtzan/resolve/main/training_args.bin
- Command line
-
hf download hf://semaj83/distilhubert-finetuned-gtzan/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/semaj83/distilhubert-finetuned-gtzan/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- d9bf362629a91134d8e37a8ec65224dbdf6212abbc52e1c1e983fa2554c6ff88
- Size of remote file:
- 4.09 kB
- SHA256:
- 341c36c7c51c08148ef7b53dcb540aa08adef2e404dc300e1948284d5e2dc30a
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