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README.md
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# F5-TTS: Fine-Tuned Arabic Speech Synthesis Model
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**License:** CC BY-NC 4.0
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**Base Model:** SWivid/F5-TTS
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## Overview
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This project fine-tunes the F5-TTS model for high-quality Arabic speech synthesis, incorporating regional diversity in pronunciation and accents. The fine-tuning process is ongoing, and temporary checkpoints are provided as progress updates. Future iterations will include improved models with enhanced accuracy and naturalness.
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This model is released under the **CC BY-NC 4.0** license, which allows free usage, modification, and distribution for **non-commercial** purposes.
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## Datasets
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Training is based on the **Common Voice Arabic Dataset
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## Model Information
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- **Base Model:** SWivid/F5-TTS
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- **Current Status:** Ongoing fine-tuning (Temporary Checkpoints Available)
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- **Batch Size:** TBD
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- **Max Samples:** TBD
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- **Training Steps:** TBD
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- *(Final training parameters will be updated upon completion of fine-tuning.)*
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## Usage Instructions
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To use the fine-tuned Arabic model, follow these steps:
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model : C:\Users\yourname\.cache\huggingface\hub\models--SWivid--F5-TTS\snapshots\995ff41929c08ff968786b448a384330438b5cb6\F5TTS_Base\model_1200000.safetensors
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```
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2. **Replace the Model File**
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- Navigate to the displayed file location.
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- Rename the existing model file:
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```
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model_1200000.safetensors → model_1200000.safetensors.bak
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```
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- Download the **Arabic checkpoint** and **vocabulary files** from this repository and place them in the same directory.
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3. **Restart the Application**
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- Relaunch the F5-TTS application to load the Arabic fine-tuned model.
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### Alternative Methods
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- **GitHub Repository:** Follow the [F5-TTS setup instructions](https://github.com/SWivid/F5-TTS), but replace the default model with the Arabic checkpoint and vocabulary files provided here.
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- Ensure **balanced audio levels** for improved synthesis quality.
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- Contributions in **dataset expansion** and **model evaluation** are highly valuable.
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If you have any questions or suggestions, feel free to reach out! 🚀
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---
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datasets:
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- mozilla-foundation/common_voice_17_0
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language:
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- ar
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base_model:
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- SWivid/F5-TTS
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pipeline_tag: text-to-speech
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tags:
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- speech
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- f5-tts
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- arabic
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---
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# F5-TTS: Fine-Tuned Arabic Speech Synthesis Model
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## Overview
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This project fine-tunes the F5-TTS model for high-quality Arabic speech synthesis, incorporating regional diversity in pronunciation and accents. The fine-tuning process is ongoing, and temporary checkpoints are provided as progress updates. Future iterations will include improved models with enhanced accuracy and naturalness.
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This model is released under the **CC BY-NC 4.0** license, which allows free usage, modification, and distribution for **non-commercial** purposes.
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## Datasets
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Training is based on the **Common Voice Arabic Dataset** so basically the model support MSA
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## Model Information
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- **Base Model:** SWivid/F5-TTS
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- **Current Status:** Ongoing fine-tuning (Temporary Checkpoints Available)
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- *(Final training parameters will be updated upon completion of fine-tuning.)*
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## Usage Instructions
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To use the fine-tuned Arabic model, follow these steps:
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model : C:\Users\yourname\.cache\huggingface\hub\models--SWivid--F5-TTS\snapshots\995ff41929c08ff968786b448a384330438b5cb6\F5TTS_Base\model_1200000.safetensors
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```
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2. **Replace the Model File**
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- Download the **Arabic checkpoint** and **vocabulary files** from this repository and place them in the same directory.
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3. **Restart the Application**
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- Relaunch the F5-TTS application to load the Arabic fine-tuned model.
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- Download the **Arabic checkpoint** and **vocabulary files** from this repository and use them instead of the basecheckpoint.
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### Alternative Methods
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- **GitHub Repository:** Follow the [F5-TTS setup instructions](https://github.com/SWivid/F5-TTS), but replace the default model with the Arabic checkpoint and vocabulary files provided here.
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- Ensure **balanced audio levels** for improved synthesis quality.
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- Contributions in **dataset expansion** and **model evaluation** are highly valuable.
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If you have any questions or suggestions, feel free to reach out! 🚀
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