Instructions to use makhataei/Wav2vec2-xlsr-Shemo-Ravdess with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use makhataei/Wav2vec2-xlsr-Shemo-Ravdess with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, Wav2Vec2ForSpeechClassification processor = AutoProcessor.from_pretrained("makhataei/Wav2vec2-xlsr-Shemo-Ravdess") model = Wav2Vec2ForSpeechClassification.from_pretrained("makhataei/Wav2vec2-xlsr-Shemo-Ravdess", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from makhataei/Wav2vec2-xlsr-Shemo-Ravdess: direct link, hf CLI and curl.
- Browser
- Download file 2.59 MB
-
https://huggingface.co/makhataei/Wav2vec2-xlsr-Shemo-Ravdess/resolve/main/tokenizer.json
- Command line
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hf download hf://makhataei/Wav2vec2-xlsr-Shemo-Ravdess/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/makhataei/Wav2vec2-xlsr-Shemo-Ravdess/resolve/main/tokenizer.json
2.59 MB
File too large to display, you can check the raw version instead.