MohamedRashad
/

Arabic-Whisper-CodeSwitching-Edition

@@ -1,199 +1,84 @@
 ---
 library_name: transformers
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 ---
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 ---
 library_name: transformers
+license: gpl-3.0
+datasets:
+- MohamedRashad/arabic-english-code-switching
+language:
+- ar
+- en
+metrics:
+- wer
+pipeline_tag: automatic-speech-recognition
 ---
+# 👳 Arabic-Whisper-CodeSwitching-Edition
+This model is a fine-tuned version of [Whisper Large v2 by OpenAI](https://huggingface.co/openai/whisper-large-v2), trained on an [Arabic-English-code-switching](https://huggingface.co/datasets/MohamedRashad/arabic-english-code-switching) dataset.
+## 📝 Model Details
 ### Model Description
+The Arabic-Whisper-CodeSwitching-Edition is designed to handle Arabic audio with embedded English words. This model enhances the original Whisper Large v2 by improving its performance on Arabic-English code-switching speech
+- **Developed by:** العبد لله
+- **Model type:** Speech Recognition
+- **Language(s) (NLP):** Arabic, English (in the context of Arabic audio)
+- **License:** GPL-3.0
 ### Model Sources [optional]
 <!-- Provide the basic links for the model. -->
 - **Repository:** [More Information Needed]
+- **Demo:** https://huggingface.co/spaces/MohamedRashad/Arabic-Whisper-CodeSwitching-Edition
+## 👷 Uses
 <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
 ### Direct Use
+The model can be used directly for transcribing Arabic speech that includes English words. It is particularly useful in multilingual environments where code-switching is common.
 ### Out-of-Scope Use
+The model may not perform well on monolingual speech in languages other than Arabic or English, or on speech with code-switching in languages other than Arabic and English.
+## 😨 Bias, Risks, and Limitations
 ### Recommendations
+Users (both direct and downstream) should be made aware of the risks, biases, and limitations of the model. More information needed for further recommendations.
+## 🔍 How to Get Started with the Model
 Use the code below to get started with the model.
+```python
+from transformers import WhisperForConditionalGeneration, WhisperProcessor
+processor = WhisperProcessor.from_pretrained("MohamedRashad/Arabic-Whisper-CodeSwitching-Edition")
+model = WhisperForConditionalGeneration.from_pretrained("MohamedRashad/Arabic-Whisper-CodeSwitching-Edition")
+# Example usage
+inputs = processor("path_to_audio_file.wav", return_tensors="pt")
+generated_ids = model.generate(inputs["input_features"])
+transcription = processor.batch_decode(generated_ids, skip_special_tokens=True)
+print(transcription)
+```
+## 👨‍🎓 Citation
+### BibTeX:
+```bibtex
+@misc{rashad2024arabicwhisper,
+  title={Arabic-Whisper-CodeSwitching-Edition},
+  author={Mohamed Rashad},
+  year={2024},
+  url={https://huggingface.co/spaces/MohamedRashad/Arabic-Whisper-CodeSwitching-Edition},
+}
+```
+### APA:
+Rashad, M. (2024). Arabic-Whisper-CodeSwitching-Edition. Retrieved from https://huggingface.co/spaces/MohamedRashad/Arabic-Whisper-CodeSwitching-Edition