Instructions to use PrachiPatel/AudioEmoDetect_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PrachiPatel/AudioEmoDetect_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="PrachiPatel/AudioEmoDetect_v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("PrachiPatel/AudioEmoDetect_v1") model = AutoModelForAudioClassification.from_pretrained("PrachiPatel/AudioEmoDetect_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from PrachiPatel/AudioEmoDetect_v1: direct link, hf CLI and curl.
- Browser
- Download file 115 MB
-
https://huggingface.co/PrachiPatel/AudioEmoDetect_v1/resolve/main/optimizer.pt
- Command line
-
hf download hf://PrachiPatel/AudioEmoDetect_v1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/PrachiPatel/AudioEmoDetect_v1/resolve/main/optimizer.pt
115 MB
- Xet hash:
- 3155f3f6ae15c3e825bf95b1cdccea0f747ea1f7790aa4b9c84ee8186454c708
- Size of remote file:
- 115 MB
- SHA256:
- fbefd7da5b53a3ea2cb011cbafc7d1f139cbc30ded5626a4ca152151b600791b
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