Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Arabic
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use deepdml/whisper-base-ar-mix-norm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepdml/whisper-base-ar-mix-norm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="deepdml/whisper-base-ar-mix-norm")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("deepdml/whisper-base-ar-mix-norm") model = AutoModelForSpeechSeq2Seq.from_pretrained("deepdml/whisper-base-ar-mix-norm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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---
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-
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- Pytorch 2.5.1+cu121
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- Datasets 3.6.0
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- Tokenizers 0.21.0
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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- Pytorch 2.5.1+cu121
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- Datasets 3.6.0
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- Tokenizers 0.21.0
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## Citation
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Please cite the model using the following BibTeX entry:
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```bibtex
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@misc{deepdml/whisper-base-ar-mix-norm,
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title={Fine-tuned Whisper base ASR model for speech recognition in Arabic},
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author={Jimenez, David},
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howpublished={\url{https://huggingface.co/deepdml/whisper-base-ar-mix-norm}},
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year={2026}
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}
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```
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