Orpheus 3b Kaya Q4 K M.gguf

🚀 Orpheus-3b-Kaya-Q4_K_M

This is a fine-tuned version of the pretrained model canopylabs/orpheus-3b-0.1-pretrained, trained on a custom voice dataset and quantised to GGUF Q4_K_M format for fast, efficient inference.

🚀 Quick Start

This model is designed for use with Orpheus-FastAPI, an OpenAI-compatible inference server for text-to-speech generation.

Compatible Inference Servers

You can load this model into:

• GPUStack
• LM Studio
• llama.cpp
• Any other GGUF-compatible OpenAI-style server

✨ Features

• Fine-tuned Version: Based on the pretrained model canopylabs/orpheus-3b-0.1-pretrained, trained on a custom voice dataset.
• Quantised Format: Quantised to GGUF Q4_K_M format for fast and efficient inference.

📦 Installation

No specific installation steps are provided in the original document.

📚 Documentation

🔧 Technical Details

📄 License

Apache License 2.0 — free for research and commercial use.

🙌 Credits

• Original model by: Canopy Labs
• Fine-tuned, quantised, and API-wrapped by: Lex-au via Unsloth and Huggingface's TRL library.

📚 Citation

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

@misc{orpheus-kaya-2025,
  author = {Lex-au},
  title = {Orpheus-3b-Kaya-Q4_K_M: Fine-Tuned TTS Model (Quantised)},
  note = {Fine-tuned from canopylabs/orpheus-3b-0.1-pt},
  year = {2025},
  publisher = {HuggingFace},
  howpublished = {\url{https://huggingface.co/lex-au/Orpheus-3b-Kaya-Q4_K_M}}
}