Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Arabic
multilingual
whisper
hf-asr-leaderboard
whisper-event
Generated from Trainer
Arabic
STT
Eval Results (legacy)
Instructions to use Salama1429/KalemaTech-Arabic-STT-ASR-based-on-Whisper-Small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Salama1429/KalemaTech-Arabic-STT-ASR-based-on-Whisper-Small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Salama1429/KalemaTech-Arabic-STT-ASR-based-on-Whisper-Small")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Salama1429/KalemaTech-Arabic-STT-ASR-based-on-Whisper-Small") model = AutoModelForSpeechSeq2Seq.from_pretrained("Salama1429/KalemaTech-Arabic-STT-ASR-based-on-Whisper-Small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9aa8c7b907e6c9a3f0b7f45b6c972e112c6fbfd509c823106d36ee86ee40834f
- Size of remote file:
- 3.58 kB
- SHA256:
- 3e614ddc46ddc60fa28212700c63037cc45bba566d130dca322893200c764cb0
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