Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Arabic
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Arbi-Houssem/TunLangModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arbi-Houssem/TunLangModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Arbi-Houssem/TunLangModel")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Arbi-Houssem/TunLangModel") model = AutoModelForSpeechSeq2Seq.from_pretrained("Arbi-Houssem/TunLangModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
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tags:
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- generated_from_trainer
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datasets:
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- Arbi-Houssem/
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metrics:
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- wer
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model-index:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name:
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type: Arbi-Houssem/
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args: 'config: ar, split: test'
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metrics:
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- name: Wer
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tags:
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- generated_from_trainer
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datasets:
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- Arbi-Houssem/comondv
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metrics:
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- wer
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model-index:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: comondv
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type: Arbi-Houssem/comondv
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args: 'config: ar, split: test'
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metrics:
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- name: Wer
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