Orpheus 3b Hindi FT Q8 0.gguf

🚀 Orpheus-3b-FT-Q8_0

Orpheus-3b-FT-Q8_0 is a quantized Text-to-Speech model. It efficiently converts text into high - quality natural speech, supporting multiple voices and emotional expressions.

✨ Features

• High - Performance TTS: Orpheus is a high - performance Text - to - Speech model fine - tuned for natural, emotional speech synthesis.
• Quantized for Efficiency: The 8 - bit quantized version of the 3B parameter model is optimized for efficiency while maintaining high - quality output.
• Multiple Voices and Emotions: Supports 1 distinct voice option with different characteristics and emotion tags like laughter, sighs, etc.
• Hardware Compatibility: Optimized for CUDA acceleration on RTX GPUs and can run on consumer hardware.
• High - Quality Audio: Produces high - quality 24kHz mono audio, fine - tuned for conversational naturalness.

📦 Installation

Compatible Inference Servers

This quantized model can be loaded into any of these LLM inference servers:

• GPUStack - GPU optimized LLM inference server (My pick) - supports LAN/WAN tensor split parallelisation
• LM Studio - Load the GGUF model and start the local server
• llama.cpp server - Run with the appropriate model parameters
• Any compatible OpenAI API - compatible server

Quick Start

1. Download this quantized model from [lex - au's Orpheus - FASTAPI collection](https://huggingface.co/collections/lex - au/orpheus - fastapi - 67e125ae03fc96dae0517707).
2. Load the model in your preferred inference server and start the server.
3. Clone the Orpheus - FastAPI repository:

git clone https://github.com/Lex - au/Orpheus - FastAPI.git
cd Orpheus - FastAPI

4. Configure the FastAPI server to connect to your inference server by setting the ORPHEUS_API_URL environment variable.
5. Follow the complete installation and setup instructions in the [repository README](https://github.com/Lex - au/Orpheus - FastAPI).

💻 Usage Examples

Basic Usage

This model is designed to be used with an LLM inference server that connects to the [Orpheus - FastAPI](https://github.com/Lex - au/Orpheus - FastAPI) frontend, which provides both a web UI and OpenAI - compatible API endpoints.

Available Voices

The model supports 1 voice:

• ऋतिका: Female, Hindi, expressive

Emotion Tags

You can add expressiveness to speech by inserting tags:

• <laugh>, <chuckle>: For laughter sounds
• <sigh>: For sighing sounds
• <cough>, <sniffle>: For subtle interruptions
• <groan>, <yawn>, <gasp>: For additional emotional expression

📚 Documentation

Model Description

Orpheus - 3b - FT - Q8_0 is a 3 billion parameter Text - to - Speech model that converts text inputs into natural - sounding speech with support for multiple voices and emotional expressions. The model has been quantized to 8 - bit (Q8_0) format for efficient inference, making it accessible on consumer hardware.

🔧 Technical Details

📄 License

This model is available under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE - 2.0).

Citation & Attribution

The original Orpheus model was created by Canopy Labs. This repository contains a quantized version optimized for use with the Orpheus - FastAPI server.

If you use this quantized model in your research or applications, please cite:

@misc{orpheus - tts - 2025,
  author = {Canopy Labs},
  title = {Orpheus - 3b - 0.1 - ft: Text - to - Speech Model},
  year = {2025},
  publisher = {HuggingFace},
  howpublished = {\url{https://huggingface.co/canopylabs/orpheus - 3b - 0.1 - ft}}
}

@misc{orpheus - quantised - 2025,
  author = {Lex - au},
  title = {Orpheus - 3b - FT - Q8_0: Quantised TTS Model with FastAPI Server},
  note = {GGUF quantisation of canopylabs/orpheus - 3b - 0.1 - ft},
  year = {2025},
  publisher = {HuggingFace},
  howpublished = {\url{https://huggingface.co/lex - au/Orpheus - 3b - FT - Q8_0.gguf}}
}

⚠️ Important Note

• Currently supports English text only.
• Best performance achieved on CUDA - compatible GPUs.
• Generation speed depends on GPU capability.