Instructions to use hughlan1214/Speech_Emotion_Recognition_wav2vec2-large-xlsr-53_240304_SER_fine-tuned2.0 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-tuned2.0 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-tuned2.0")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hughlan1214/Speech_Emotion_Recognition_wav2vec2-large-xlsr-53_240304_SER_fine-tuned2.0") model = AutoModelForAudioClassification.from_pretrained("hughlan1214/Speech_Emotion_Recognition_wav2vec2-large-xlsr-53_240304_SER_fine-tuned2.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e218d52baf80826c5a7f6e55787edf55054001608cfe6e837d155c9fd9bb85c5
- Size of remote file:
- 1.26 GB
- SHA256:
- 9e0d8f1a1bcb89cba546f3e0ad6816d3d823431aef1a2a6e1f22ebf5bb1a55ef
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