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 pytorch_model.bin from PrachiPatel/AudioEmoDetect_v1: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/PrachiPatel/AudioEmoDetect_v1/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://PrachiPatel/AudioEmoDetect_v1@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/PrachiPatel/AudioEmoDetect_v1/resolve/refs%2Fpr%2F2/pytorch_model.bin
378 MB
- Xet hash:
- 29b2b4a800d9daad4d2d7b11ad2e1e0e07988a9b7bb9873bdbfc65e52d281735
- Size of remote file:
- 378 MB
- SHA256:
- f623bc36959cc7f8aedef6b9b6c2ce483dc6ddb71df8f59cf2e972ac4e154016
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