Update README.md

README.md

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----
-license: apache-2.0
----
+---
+language: en
+tags:
+- text-to-speech
+- tts
+- audio
+- speech-synthesis
+- orpheus
+- gguf
+license: apache-2.0
+datasets:
+- internal
+---
+
+# Orpheus-3b-FT-Q2_K
+
+This is a quantised version of [canopylabs/orpheus-3b-0.1-ft](https://huggingface.co/canopylabs/orpheus-3b-0.1-ft).
+
+Orpheus is a high-performance Text-to-Speech model fine-tuned for natural, emotional speech synthesis. This repository hosts the 8-bit quantised version of the 3B parameter model, optimised for efficiency while maintaining high-quality output.
+
+## Model Description
+
+**Orpheus-3b-FT-Q2_K** 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 quantised to 8-bit (Q2_K) format for efficient inference, making it accessible on consumer hardware.
+
+Key features:
+- 8 distinct voice options with different characteristics
+- Support for emotion tags like laughter, sighs, etc.
+- Optimised for CUDA acceleration on RTX GPUs
+- Produces high-quality 24kHz mono audio
+- Fine-tuned for conversational naturalness
+
+## How to Use
+
+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.
+
+### Compatible Inference Servers
+
+This quantised model can be loaded into any of these LLM inference servers:
+
+- [GPUStack](https://github.com/gpustack/gpustack) - GPU optimised LLM inference server (My pick) - supports LAN/WAN tensor split parallelisation
+- [LM Studio](https://lmstudio.ai/) - Load the GGUF model and start the local server
+- [llama.cpp server](https://github.com/ggerganov/llama.cpp) - Run with the appropriate model parameters
+- Any compatible OpenAI API-compatible server
+
+### Quick Start
+
+1. Download this quantised 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:
+```bash
+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).
+
+### Audio Samples
+
+Listen to the model in action with different voices and emotions:
+
+#### Default Voice Sample
+<audio controls>
+  <source src="https://lex-au.github.io/Orpheus-FastAPI/DefaultTest.mp3" type="audio/mpeg">
+  Your browser does not support the audio element.
+</audio>
+
+#### Leah (Happy)
+<audio controls>
+  <source src="https://lex-au.github.io/Orpheus-FastAPI/LeahHappy.mp3" type="audio/mpeg">
+  Your browser does not support the audio element.
+</audio>
+
+#### Tara (Sad)
+<audio controls>
+  <source src="https://lex-au.github.io/Orpheus-FastAPI/TaraSad.mp3" type="audio/mpeg">
+  Your browser does not support the audio element.
+</audio>
+
+#### Zac (Contemplative)
+<audio controls>
+  <source src="https://lex-au.github.io/Orpheus-FastAPI/ZacContemplative.mp3" type="audio/mpeg">
+  Your browser does not support the audio element.
+</audio>
+
+### Available Voices
+
+The model supports 8 different voices:
+- `tara`: Female, conversational, clear
+- `leah`: Female, warm, gentle
+- `jess`: Female, energetic, youthful
+- `leo`: Male, authoritative, deep
+- `dan`: Male, friendly, casual
+- `mia`: Female, professional, articulate
+- `zac`: Male, enthusiastic, dynamic
+- `zoe`: Female, calm, soothing
+
+### 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
+
+## Technical Specifications
+
+- **Architecture**: Specialised token-to-audio sequence model
+- **Parameters**: ~3 billion
+- **Quantisation**: 8-bit (GGUF Q2_K format)
+- **Audio Sample Rate**: 24kHz
+- **Input**: Text with optional voice selection and emotion tags
+- **Output**: High-quality WAV audio
+- **Language**: English
+- **Hardware Requirements**: CUDA-compatible GPU (recommended: RTX series)
+- **Integration Method**: External LLM inference server + Orpheus-FastAPI frontend
+
+## Limitations
+
+- Currently supports English text only
+- Best performance achieved on CUDA-compatible GPUs
+- Generation speed depends on GPU capability
+
+## 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 quantised version optimised for use with the Orpheus-FastAPI server.
+
+If you use this quantised 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-Q2_K: 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-Q4_K_M.gguf}}
+}
+```