Instructions to use MariaK/distilhubert-finetuned-gtzan-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MariaK/distilhubert-finetuned-gtzan-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="MariaK/distilhubert-finetuned-gtzan-test")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("MariaK/distilhubert-finetuned-gtzan-test") model = AutoModelForAudioClassification.from_pretrained("MariaK/distilhubert-finetuned-gtzan-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from MariaK/distilhubert-finetuned-gtzan-test: direct link, hf CLI and curl.
- Browser
- Download file 94.8 MB
-
https://huggingface.co/MariaK/distilhubert-finetuned-gtzan-test/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://MariaK/distilhubert-finetuned-gtzan-test/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/MariaK/distilhubert-finetuned-gtzan-test/resolve/main/pytorch_model.bin
94.8 MB
- Xet hash:
- 006bcdc37871b3191def6846ba6861e724ec9d16b50c64441272f279c782aabb
- Size of remote file:
- 94.8 MB
- SHA256:
- cabedda18859aa7803106c6a0337774b0d37e17719a3949fd3ef2c1796a16ac0
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