Update README.md

README.md

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----
-license: gpl-3.0
----
+---
+license: gpl-3.0
+datasets:
+- ai4bharat/IndicVoices
+language:
+- hi
+- bn
+- ta
+- te
+- ml
+- kn
+- gu
+- mr
+- or
+- pa
+- as
+- en
+base_model:
+- Plachta/Seed-VC
+pipeline_tag: audio-to-audio
+tags:
+- voice-conversion
+- Voice-Changer
+- Voice
+---
+
+# IndicVoiceChanger
+
+**IndicVoiceChanger** is a finetuned version of the [Seed Voice Conversion](https://huggingface.co/Plachta/Seed-VC/tree/main) model, adapted for Indian languages.  
+It enables high-quality voice conversion across multiple Indian languages, preserving speaker identity while changing the voice characteristics.
+
+## Overview
+This model is built upon the Seed Voice Conversion checkpoints and finetuned with a mix of publicly available open-source datasets and our own proprietary dataset.  
+It is designed to work well on speech data from diverse Indian languages, accents, and speaking styles.
+
+## Try It Out
+
+Experience the model firsthand at: **[Hugging Face Spaces Demo](https://huggingface.co/spaces/DreamSyncCo/IndicVoiceChanger)**
+
+## Fine-tuning on Custom Data
+
+While the zero shot performance of this model is usually good, it can be further improved with fine-tuning. This model supports efficient fine-tuning on your custom speakers with remarkable data efficiency and speed:
+
+- **Minimal Data Requirements**: Train on new speakers with as little as **1 utterance per speaker**
+- **Ultra-Fast Training**: Achieve good results in just **100 training steps** (approximately **2 minutes on T4 GPU**)
+- **Speaker Adaptation**: Significantly improve performance on specific target speakers through personalized fine-tuning
+
+### Getting Started with Fine-tuning
+
+For detailed instructions on installation, usage, and fine-tuning, please refer to the comprehensive guide at: **https://github.com/Plachtaa/seed-vc**
+
+**Note**: We will be updating this repository with example notebooks demonstrating the fine-tuning process soon.
+
+**Important**: When fine-tuning for Indian languages, make sure to use the checkpoints provided in this repository as your starting point for optimal performance.
+
+## Acknowledgments
+
+Special thanks to the [SeedVC](https://github.com/Plachtaa/seed-vc) project for providing the foundational architecture and training framework that made this Indian language adaptation possible.
+