Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Arabic
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use saralameri/whisper-tiny-ar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saralameri/whisper-tiny-ar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="saralameri/whisper-tiny-ar")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("saralameri/whisper-tiny-ar") model = AutoModelForSpeechSeq2Seq.from_pretrained("saralameri/whisper-tiny-ar", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.bin from saralameri/whisper-tiny-ar: direct link, hf CLI and curl.
- Browser
- Download file 151 MB
-
https://huggingface.co/saralameri/whisper-tiny-ar/resolve/main/model.bin
- Command line
-
hf download hf://saralameri/whisper-tiny-ar/model.bin
-
curl -L -o model.bin https://huggingface.co/saralameri/whisper-tiny-ar/resolve/main/model.bin
151 MB
- Xet hash:
- 714aeb645ac4a6c9210f7d22e306ea8c0f25a44b9dbe3819eef7a5a4b14a5bb1
- Size of remote file:
- 151 MB
- SHA256:
- 10eeb2732b6f64f2391a9adabe3054bd68a45b0a9ecfa406dd179d93b381b860
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