Instructions to use somosnlp-hackathon-2022/wav2vec2-base-finetuned-sentiment-classification-MESD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use somosnlp-hackathon-2022/wav2vec2-base-finetuned-sentiment-classification-MESD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="somosnlp-hackathon-2022/wav2vec2-base-finetuned-sentiment-classification-MESD")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("somosnlp-hackathon-2022/wav2vec2-base-finetuned-sentiment-classification-MESD") model = AutoModelForAudioClassification.from_pretrained("somosnlp-hackathon-2022/wav2vec2-base-finetuned-sentiment-classification-MESD") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#2 opened over 2 years ago
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librarian-bot