Instructions to use quaja/hubert-split-data-base-amharic-speech-emotion-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use quaja/hubert-split-data-base-amharic-speech-emotion-recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="quaja/hubert-split-data-base-amharic-speech-emotion-recognition")# Load model directly from transformers import AutoProcessor, HubertForSpeechClassification processor = AutoProcessor.from_pretrained("quaja/hubert-split-data-base-amharic-speech-emotion-recognition") model = HubertForSpeechClassification.from_pretrained("quaja/hubert-split-data-base-amharic-speech-emotion-recognition") - Notebooks
- Google Colab
- Kaggle
model_name_or_path = "quaja/hubert-base-amharic-speech-emotion-recognition" config = AutoConfig.from_pretrained(model_name_or_path) feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(model_name_or_path) sampling_rate = feature_extractor.sampling_rate model = HubertForSpeechClassification.from_pretrained(model_name_or_path)
- Downloads last month
- 6