Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
whisper-event
Generated from Trainer
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use arbml/whisper-small-ar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arbml/whisper-small-ar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="arbml/whisper-small-ar")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("arbml/whisper-small-ar") model = AutoModelForSpeechSeq2Seq.from_pretrained("arbml/whisper-small-ar", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| cd ~ | |
| sudo add-apt-repository -y ppa:jonathonf/ffmpeg-4 | |
| sudo apt update | |
| sudo apt install -y ffmpeg | |
| sudo apt-get install git-lfs | |
| env_name=whisper | |
| python3 -m venv $env_name | |
| echo "source ~/$env_name/bin/activate" >> ~/.bashrc | |
| cd whisper_sprint | |
| bash |