Audio Classification
Transformers
Safetensors
audio-spectrogram-transformer
speech-emotion-recognition
yoruba
code-switching
multilingual
ssast
nigeria
Eval Results (legacy)
Instructions to use LyngualLabs/YORENG100-SSAST-Emotion-Recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LyngualLabs/YORENG100-SSAST-Emotion-Recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="LyngualLabs/YORENG100-SSAST-Emotion-Recognition")# pip install -U transformers accelerate # Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("LyngualLabs/YORENG100-SSAST-Emotion-Recognition") model = AutoModelForAudioClassification.from_pretrained("LyngualLabs/YORENG100-SSAST-Emotion-Recognition", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from LyngualLabs/YORENG100-SSAST-Emotion-Recognition: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/LyngualLabs/YORENG100-SSAST-Emotion-Recognition/resolve/main/training_args.bin
- Command line
-
hf download hf://LyngualLabs/YORENG100-SSAST-Emotion-Recognition/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/LyngualLabs/YORENG100-SSAST-Emotion-Recognition/resolve/main/training_args.bin
5.2 kB
- Xet hash:
- 077e7aa301b09ea1a9cd6cd8a564aac7d63f54780dd7ea201b78aaa73f0facc7
- Size of remote file:
- 5.2 kB
- SHA256:
- 8584a37043866b1ded9e129ff87acd61593751c9f27850efe3373e3a3baf2129
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