Instructions to use unsloth/orpheus-3b-0.1-ft-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use unsloth/orpheus-3b-0.1-ft-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-to-speech", model="unsloth/orpheus-3b-0.1-ft-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("unsloth/orpheus-3b-0.1-ft-GGUF", dtype="auto")

llama-cpp-python

How to use unsloth/orpheus-3b-0.1-ft-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="unsloth/orpheus-3b-0.1-ft-GGUF",
	filename="orpheus-3b-0.1-ft-F16.gguf",
)

llm.create_chat_completion(
	messages = "\"The answer to the universe is 42\""
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use unsloth/orpheus-3b-0.1-ft-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf unsloth/orpheus-3b-0.1-ft-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
llama-cli -hf unsloth/orpheus-3b-0.1-ft-GGUF:UD-Q4_K_XL

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf unsloth/orpheus-3b-0.1-ft-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
llama-cli -hf unsloth/orpheus-3b-0.1-ft-GGUF:UD-Q4_K_XL

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf unsloth/orpheus-3b-0.1-ft-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
./llama-cli -hf unsloth/orpheus-3b-0.1-ft-GGUF:UD-Q4_K_XL

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf unsloth/orpheus-3b-0.1-ft-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
./build/bin/llama-cli -hf unsloth/orpheus-3b-0.1-ft-GGUF:UD-Q4_K_XL

Use Docker

docker model run hf.co/unsloth/orpheus-3b-0.1-ft-GGUF:UD-Q4_K_XL

LM Studio
Jan
Ollama
How to use unsloth/orpheus-3b-0.1-ft-GGUF with Ollama:
```
ollama run hf.co/unsloth/orpheus-3b-0.1-ft-GGUF:UD-Q4_K_XL
```

Unsloth Studio

How to use unsloth/orpheus-3b-0.1-ft-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for unsloth/orpheus-3b-0.1-ft-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for unsloth/orpheus-3b-0.1-ft-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for unsloth/orpheus-3b-0.1-ft-GGUF to start chatting

How to use unsloth/orpheus-3b-0.1-ft-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf unsloth/orpheus-3b-0.1-ft-GGUF:UD-Q4_K_XL

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "unsloth/orpheus-3b-0.1-ft-GGUF:UD-Q4_K_XL"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use unsloth/orpheus-3b-0.1-ft-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf unsloth/orpheus-3b-0.1-ft-GGUF:UD-Q4_K_XL

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default unsloth/orpheus-3b-0.1-ft-GGUF:UD-Q4_K_XL

Run Hermes

hermes

Atomic Chat new
Docker Model Runner
How to use unsloth/orpheus-3b-0.1-ft-GGUF with Docker Model Runner:
```
docker model run hf.co/unsloth/orpheus-3b-0.1-ft-GGUF:UD-Q4_K_XL
```

Lemonade

How to use unsloth/orpheus-3b-0.1-ft-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull unsloth/orpheus-3b-0.1-ft-GGUF:UD-Q4_K_XL

Run and chat with the model

lemonade run user.orpheus-3b-0.1-ft-GGUF-UD-Q4_K_XL

List all available models

lemonade list

Orpheus 3B 0.1 Finetuned

03/18/2025 – We are releasing our 3B Orpheus TTS model with additional finetunes. Code is available on GitHub: CanopyAI/Orpheus-TTS

Orpheus TTS is a state-of-the-art, Llama-based Speech-LLM designed for high-quality, empathetic text-to-speech generation. This model has been finetuned to deliver human-level speech synthesis, achieving exceptional clarity, expressiveness, and real-time streaming performances.

Model Details

Model Capabilities

Human-Like Speech: Natural intonation, emotion, and rhythm that is superior to SOTA closed source models
Zero-Shot Voice Cloning: Clone voices without prior fine-tuning
Guided Emotion and Intonation: Control speech and emotion characteristics with simple tags
Low Latency: ~200ms streaming latency for realtime applications, reducible to ~100ms with input streaming

Model Sources

GitHub Repo: https://github.com/canopyai/Orpheus-TTS
Blog Post: https://canopylabs.ai/model-releases
Colab Inference Notebook: notebook link

Usage

Check out our Colab (link to Colab) or GitHub (link to GitHub) on how to run easy inference on our finetuned models.

Model Misuse

Do not use our models for impersonation without consent, misinformation or deception (including fake news or fraudulent calls), or any illegal or harmful activity. By using this model, you agree to follow all applicable laws and ethical guidelines. We disclaim responsibility for any use.