Instructions to use werent4/emo-gliclass-audio-bi-1-wds-0.015-red-sum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use werent4/emo-gliclass-audio-bi-1-wds-0.015-red-sum with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("werent4/emo-gliclass-audio-bi-1-wds-0.015-red-sum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from werent4/emo-gliclass-audio-bi-1-wds-0.015-red-sum: direct link, hf CLI and curl.
- Browser
- Download file 3.58 MB
-
https://huggingface.co/werent4/emo-gliclass-audio-bi-1-wds-0.015-red-sum/resolve/main/tokenizer.json
- Command line
-
hf download hf://werent4/emo-gliclass-audio-bi-1-wds-0.015-red-sum/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/werent4/emo-gliclass-audio-bi-1-wds-0.015-red-sum/resolve/main/tokenizer.json
3.58 MB
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