Instructions to use hughlan1214/Speech_Emotion_Recognition_wav2vec2-large-xlsr-53_240304_SER_fine-tuned1.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hughlan1214/Speech_Emotion_Recognition_wav2vec2-large-xlsr-53_240304_SER_fine-tuned1.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hughlan1214/Speech_Emotion_Recognition_wav2vec2-large-xlsr-53_240304_SER_fine-tuned1.1")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hughlan1214/Speech_Emotion_Recognition_wav2vec2-large-xlsr-53_240304_SER_fine-tuned1.1") model = AutoModelForAudioClassification.from_pretrained("hughlan1214/Speech_Emotion_Recognition_wav2vec2-large-xlsr-53_240304_SER_fine-tuned1.1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c8cadae2677cc23266b05641bc2d030ee096b00fed30aec5580c627c6934a722
- Size of remote file:
- 1.26 GB
- SHA256:
- 33920cd1d1f2a19c072eb48f154326865d5a8bf10e79810a9959a9f5773ed722
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