Instructions to use IbrahimAmin/hubert-arabic-spoken-dialect-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IbrahimAmin/hubert-arabic-spoken-dialect-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="IbrahimAmin/hubert-arabic-spoken-dialect-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("IbrahimAmin/hubert-arabic-spoken-dialect-classifier") model = AutoModelForAudioClassification.from_pretrained("IbrahimAmin/hubert-arabic-spoken-dialect-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from IbrahimAmin/hubert-arabic-spoken-dialect-classifier: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/IbrahimAmin/hubert-arabic-spoken-dialect-classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://IbrahimAmin/hubert-arabic-spoken-dialect-classifier/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/IbrahimAmin/hubert-arabic-spoken-dialect-classifier/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- 9ae53e405775350482872bb38c044f722d2f473c7a67d76db6067618cec2ee4c
- Size of remote file:
- 378 MB
- SHA256:
- 7b5cbb2c8bb71ee5c16cb61dc733ce4b5695987c281763265707e3fb110350fc
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