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 model.safetensors 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/model.safetensors
- Command line
-
hf download hf://IbrahimAmin/hubert-arabic-spoken-dialect-classifier/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/IbrahimAmin/hubert-arabic-spoken-dialect-classifier/resolve/main/model.safetensors
378 MB
- Xet hash:
- ed28aa58f147633b3a8f6e06b7c5a1cafd99a408bb588818de404d07e484e174
- Size of remote file:
- 378 MB
- SHA256:
- 6c07e719f744d99548d518687438c30aae12f82d9d7af8866ea761260dd3c418
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.