Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Arabic
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use hkhdair/whisper-small-ar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hkhdair/whisper-small-ar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hkhdair/whisper-small-ar")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hkhdair/whisper-small-ar") model = AutoModelForSpeechSeq2Seq.from_pretrained("hkhdair/whisper-small-ar", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hkhdair/whisper-small-ar: direct link, hf CLI and curl.
- Browser
- Download file 967 MB
-
https://huggingface.co/hkhdair/whisper-small-ar/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hkhdair/whisper-small-ar/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hkhdair/whisper-small-ar/resolve/main/pytorch_model.bin
967 MB
- Xet hash:
- c30842990e743183db8c3a2415ad914da6a77d1baf3452f8a06a548fb01c8fd9
- Size of remote file:
- 967 MB
- SHA256:
- af1f1af380cb1871125972642d90de884fe78778c324706ff59c83680e81d103
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