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vinhnx90/VT-Orpheus-3B-TTS-Ceylia-Q4KM-GGUFF

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face
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Introduction

VT-Orpheus-3B-TTS-lora-adapter is a Lora adapter fine-tuned from Orpheus-TTS.

Dataset is from <https://huggingface.co/datasets/Jinsaryko/Ceylia>.

Sample Audio

Check my setup guide for running the local Orpheus model with my Lora adapter.

python
python gguf_orpheus.py --text "Seriously? <giggle> That's the cutest thing I've ever heard ! " --voice ceylia

<audio controls><source src="https://huggingface.co/vinhnx90/VT-Orpheus-3B-TTS-Ceylia-Q4KM-GGUFF/resolve/main/output.wav" type="audio/wav"></audio>

python
python gguf_orpheus.py --text "Hi! I'm Ceylia. <laugh> This is so exciting! <giggle>" --voice ceylia

<audio controls><source src="https://huggingface.co/vinhnx90/VT-Orpheus-3B-TTS-Ceylia-Q4KM-GGUFF/resolve/main/ceylia20250409010117.wav" type="audio/wav"></audio>

python
python gguf_orpheus.py --text "Morning! <giggle> I finally finished that project last night. It took forever, but the results look amazing. <yawn> Sorry, still a bit tired from staying up so late." --voice ceylia

<audio controls><source src="https://huggingface.co/vinhnx90/VT-Orpheus-3B-TTS-Ceylia-Q4KM-GGUFF/resolve/main/ceylia20250409013043.wav" type="audio/wav"></audio>

Running Locally

This section provides a step-by-step guide to running the VT-Orpheus-3B-TTS-Ceylia.Q4_K_M.gguf model locally on your machine. There are two main methods to run this model:

Method 1: Using LM Studio (Recommended for beginners)

Prerequisites

  1. 1.LM Studio installed on your computer
  2. 2.Python 3.8+ installed
  3. 3.The VT-Orpheus-3B-TTS-Ceylia.Q4_K_M.gguf model file

Setup Steps

  1. 1.Install LM Studio
  2. 2.Download and install LM Studio from lmstudio.ai
  3. 3.Launch LM Studio
  1. 1.Load the GGUF model
  2. 2.In LM Studio, click "Add Model"
  3. 3.Select the VT-Orpheus-3B-TTS-Ceylia.Q4_K_M.gguf file from your computer
  4. 4.Once added, click on the model to load it
  1. 1.Start the local server
  2. 2.Go to the "Local Server" tab in LM Studio
  3. 3.Click "Start Server" to launch the local API server (default address is http://127.0.0.1:1234)
  1. 1.Clone orpheus-tts-local repository
bash
git clone https://github.com/isaiahbjork/orpheus-tts-local.git
cd orpheus-tts-local
  1. 1.Install dependencies
bash
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt

5.1 Edit gguf_orpheus.py to include new ceylia voice

Open gguf_orpheus.py file in ./orpheus-tts-local directory, find the line of AVAILABLE_VOICES and DEFAULT_VOICE and edit to include ceylia voice, default is tara.

python
# Available voices based on the Orpheus-TTS repository
AVAILABLE_VOICES = ["tara", "leah", "jess", "leo", "dan", "mia", "zac", "zoe", "ceylia"]
DEFAULT_VOICE = "ceylia"

Save the file gguf_orpheus.py.

  1. 1.Run the model
bash
python gguf_orpheus.py --text "Hi! I'm Ceylia. <laugh> This is so exciting! <giggle>" --voice ceylia --output output.wav

Available Parameters

  • —--text: The text to convert to speech (required)
  • —--voice: The voice to use (default is "tara", but use "ceylia" for this model)
  • —--output: Output WAV file path (default: auto-generated filename)
  • —--temperature: Temperature for generation (default: 0.6)
  • —--top_p: Top-p sampling parameter (default: 0.9)
  • —--repetition_penalty: Repetition penalty (default: 1.1)
  • —--backend: Specify the backend (default: "lmstudio", also supports "ollama")

Method 2: Using llama.cpp directly

Prerequisites

  1. 1.llama.cpp installed and built on your system
  2. 2.The VT-Orpheus-3B-TTS-Ceylia.Q4_K_M.gguf model file

Setup Steps

  1. 1.Clone and build llama.cpp
bash
git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp
cmake -B build
cmake --build build --config Release
  1. 1.Start the server
bash
./llama-server -m /path/to/VT-Orpheus-3B-TTS-Ceylia.Q4_K_M.gguf --port 8080
  1. 1.Clone orpheus-tts-local repository
bash
git clone https://github.com/isaiahbjork/orpheus-tts-local.git
cd orpheus-tts-local
  1. 1.Install dependencies
bash
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt
  1. 1.Run the model with custom API URL
bash
python gguf_orpheus.py --text "Hi! I'm Ceylia. <laugh> Let's play! <sniffle> This is so exciting! <giggle>" --voice ceylia --output output.wav --api_url http://localhost:8080/v1

Emotion Tags

You can add emotion to the speech by including the following tags in your text:

  • —<giggle>
  • —<laugh>
  • —<chuckle>
  • —<sigh>
  • —<cough>
  • —<sniffle>
  • —<groan>
  • —<yawn>
  • —<gasp>

Example:

bash
python gguf_orpheus.py --text "Hi! I'm Ceylia. <laugh> This is so exciting! <giggle>" --voice ceylia

Troubleshooting

  1. 1.Error connecting to server: Make sure LM Studio's server is running or llama.cpp server is running on the correct port
  2. 2.Low-quality audio: Try adjusting the temperature (higher = more variance) or repetition_penalty (>1.1 recommended)
  3. 3.Slow generation: Reduce model precision or run on a more powerful GPU if available

Uploaded model

  • —Developed by: vinhnx90
  • —License: apache-2.0
  • —Finetuned from model : unsloth/orpheus-3b-0.1-ft-unsloth-bnb-4bit

This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.

<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>