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README.md

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----
-license: apache-2.0
----
+---
+license: other
+license_name: coqui-public-model-license
+license_link: https://coqui.ai/cpml
+library_name: coqui
+pipeline_tag: text-to-speech
+widget:
+  - text: "Once when I was six years old I saw a magnificent picture"
+---
+
+# XTTS v2 Fine-Tuned on Hindi Datasets
+
+**Model Name**: XTTS v2 Fine-Tuned on Hindi Datasets
+
+**Model Description**: This is a fine-tuned version of the XTTS v2 (Cross-lingual Text-to-Speech) model developed by Coqui-AI, specifically fine-tuned on Hindi speech datasets to improve performance in generating natural and accurate Hindi speech. The model supports a range of features including voice cloning and multilingual speech generation.
+
+### Features
+- **Languages**: Supports 17 languages including Hindi (hi).
+- **Voice Cloning**: Clone voices with just a 6-second audio clip.
+- **Emotion and Style Transfer**: Achieve emotion and style transfer by cloning.
+- **Cross-Language Voice Cloning**: Supports voice cloning across different languages.
+- **Sampling Rate**: 24kHz sampling rate for high-quality audio.
+
+### Updates over XTTS-v1
+- **New Languages**: Added support for Hungarian and Korean.
+- **Architectural Improvements**: Enhanced speaker conditioning and interpolation.
+- **Stability Improvements**: Better overall stability and performance.
+- **Audio Quality**: Improved prosody and audio quality.
+
+### Languages
+The XTTS-v2 model supports 17 languages including:
+- **English (en)**
+- **Spanish (es)**
+- **French (fr)**
+- **German (de)**
+- **Italian (it)**
+- **Portuguese (pt)**
+- **Polish (pl)**
+- **Turkish (tr)**
+- **Russian (ru)**
+- **Dutch (nl)**
+- **Czech (cs)**
+- **Arabic (ar)**
+- **Chinese (zh-cn)**
+- **Japanese (ja)**
+- **Hungarian (hu)**
+- **Korean (ko)**
+- **Hindi (hi)**
+
+### Training Data
+The model was fine-tuned on the following Hindi datasets:
+- **Mozilla CommonVoice 18**: A diverse dataset of Hindi speech.
+- **IndicTTS Hindi Dataset**: Hindi speech data for text-to-speech training.
+
+### Code
+The [code-base](https://github.com/coqui-ai/TTS) supports both inference and [fine-tuning](https://tts.readthedocs.io/en/latest/models/xtts.html#training).
+
+### Demo Spaces
+- [XTTS Space](https://huggingface.co/spaces/coqui/xtts): Explore the model's performance on supported languages and try it with your own reference or microphone input.
+- [XTTS Voice Chat with Mistral or Zephyr](https://huggingface.co/spaces/coqui/voice-chat-with-mistral): Experience streaming voice chat with Mistral 7B Instruct or Zephyr 7B Beta.
+
+### License
+This model is licensed under the [Coqui Public Model License](https://coqui.ai/cpml). Read more about the [origin story of CPML here](https://coqui.ai/blog/tts/cpml).
+
+### Contact
+Join our 🐸 Community on [Discord](https://discord.gg/fBC58unbKE) and follow us on [Twitter](https://twitter.com/coqui_ai). For inquiries, you can also email us at [email protected].
+
+### Colab Notebook
+You can view the Colab notebook used for fine-tuning the XTTS v2 model on Hindi datasets and replicate the process by following this [Colab Notebook Link](https://colab.research.google.com/drive/1VwNltFIcqhB7Ydt4NVaPnYegl-qHoUSO#scrollTo=KKj-kq7iCG3d).
+
+### Usage
+
+#### Using 🐸TTS API
+```python
+from TTS.api import TTS
+
+# Load the model
+tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2", gpu=True)
+
+# Generate speech by cloning a voice using default settings
+tts.tts_to_file(
+    text="It took me quite a long time to develop a voice, and now that I have it I'm not going to be silent.",
+    file_path="output.wav",
+    speaker_wav="/path/to/target/speaker.wav",
+    language="hi"
+)