Instructions to use sarthak712/emotion_detection_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sarthak712/emotion_detection_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="sarthak712/emotion_detection_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("sarthak712/emotion_detection_model") model = AutoModelForAudioClassification.from_pretrained("sarthak712/emotion_detection_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sarthak712/emotion_detection_model: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/sarthak712/emotion_detection_model/resolve/main/training_args.bin
- Command line
-
hf download hf://sarthak712/emotion_detection_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sarthak712/emotion_detection_model/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- f95c9e93647bba74f65cf2460c8ddd0b7631d227261551ef438fb616d2f7f432
- Size of remote file:
- 4.73 kB
- SHA256:
- 98633ba79364d2d285800bddf55c34728c8794144c36bfb122fcc8a4364668f1
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