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

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

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

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

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

Setup Steps

1. Install LM Studio

• Download and install LM Studio from lmstudio.ai
• Launch LM Studio

2. Load the GGUF model

• In LM Studio, click "Add Model"
• Select the VT-Orpheus-3B-TTS-Ceylia.Q4_K_M.gguf file from your computer
• Once added, click on the model to load it

3. Start the local server

• Go to the "Local Server" tab in LM Studio
• Click "Start Server" to launch the local API server (default address is http://127.0.0.1:1234)

4. Clone orpheus-tts-local repository

git clone https://github.com/isaiahbjork/orpheus-tts-local.git
cd orpheus-tts-local

5. Install dependencies

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.

# 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.

6. Run the model

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

Setup Steps

1. Clone and build llama.cpp

git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp
cmake -B build
cmake --build build --config Release

2. Start the server

./llama-server -m /path/to/VT-Orpheus-3B-TTS-Ceylia.Q4_K_M.gguf --port 8080

3. Clone orpheus-tts-local repository

git clone https://github.com/isaiahbjork/orpheus-tts-local.git
cd orpheus-tts-local

4. Install dependencies

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt

5. Run the model with custom API URL

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:

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

Troubleshooting

1. Error connecting to server: Make sure LM Studio's server is running or llama.cpp server is running on the correct port
2. Low-quality audio: Try adjusting the temperature (higher = more variance) or repetition_penalty (>1.1 recommended)
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.