Audio Classification
Transformers
Safetensors
English
wav2vec2
emotion
audio
classification
music
facebook
Instructions to use prithivMLmods/Speech-Emotion-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Speech-Emotion-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="prithivMLmods/Speech-Emotion-Classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Speech-Emotion-Classification") model = AutoModelForAudioClassification.from_pretrained("prithivMLmods/Speech-Emotion-Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-3750/scaler.pt from prithivMLmods/Speech-Emotion-Classification: direct link, hf CLI and curl.
- Browser
- Download file 988 Bytes
-
https://huggingface.co/prithivMLmods/Speech-Emotion-Classification/resolve/main/checkpoint-3750/scaler.pt
- Command line
-
hf download hf://prithivMLmods/Speech-Emotion-Classification/checkpoint-3750/scaler.pt
-
curl -L -o scaler.pt https://huggingface.co/prithivMLmods/Speech-Emotion-Classification/resolve/main/checkpoint-3750/scaler.pt
988 Bytes
- Xet hash:
- db489661463c6acfb9bdccd9f3e432991711597921e5e6f8577a1dca24c0ff9d
- Size of remote file:
- 988 Bytes
- SHA256:
- c357e3fcd5a4026c6fbfc21f6d0286251977d70579d35af48fb93121ca019e2d
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