Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use akhooli/whisper-small-ar2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akhooli/whisper-small-ar2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="akhooli/whisper-small-ar2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("akhooli/whisper-small-ar2") model = AutoModelForSpeechSeq2Seq.from_pretrained("akhooli/whisper-small-ar2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from akhooli/whisper-small-ar2: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/akhooli/whisper-small-ar2/resolve/main/training_args.bin
- Command line
-
hf download hf://akhooli/whisper-small-ar2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/akhooli/whisper-small-ar2/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- e6e63f4ff2f50d77ebb2c2e9e06ad571e3fc33089990fada0efae988a823e190
- Size of remote file:
- 5.5 kB
- SHA256:
- 4e772c543d3aac70983d28ae127809cf921c485c16c8e955bf87d63d14d9060f
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