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:
- 4f96d72bdeb2a80092ead389b8f442591e799a62aa6f8ab959d4f6783c75e71e
- Size of remote file:
- 967 MB
- SHA256:
- cdbaf0222f3b08318d094759f65dad650322cd4e9a914b6b77db0d00b7ec3c3e
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