Instructions to use ThorBaller/Clarinet_note_identifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThorBaller/Clarinet_note_identifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="ThorBaller/Clarinet_note_identifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ThorBaller/Clarinet_note_identifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from ThorBaller/Clarinet_note_identifier: direct link, hf CLI and curl.
- Browser
- Download file 97 Bytes
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https://huggingface.co/ThorBaller/Clarinet_note_identifier/resolve/main/README.md
- Command line
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hf download hf://ThorBaller/Clarinet_note_identifier/README.md
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curl -L -H "Authorization: Bearer $HF_TOKEN" -o README.md https://huggingface.co/ThorBaller/Clarinet_note_identifier/resolve/main/README.md
97 Bytes
metadata
license: mit
language:
- en
library_name: transformers
pipeline_tag: audio-classification