Instructions to use isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF with Transformers:

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

pipe = pipeline("text-to-speech", model="isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF", dtype="auto")

llama-cpp-python

How to use isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF",
	filename="orpheus-3b-0.1-ft-q4_k_m.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 isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF:Q4_K_M

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 isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF:Q4_K_M

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 isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF:Q4_K_M

Use Docker

docker model run hf.co/isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF with Ollama:
```
ollama run hf.co/isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF:Q4_K_M
```

Unsloth Studio

How to use isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-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 isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-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 isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF to start chatting

How to use isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF:Q4_K_M

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": "isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-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 isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF:Q4_K_M

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 isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat new
Docker Model Runner
How to use isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF with Docker Model Runner:
```
docker model run hf.co/isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF:Q4_K_M
```

Lemonade

How to use isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.orpheus-3b-0.1-ft-Q4_K_M-GGUF-Q4_K_M

List all available models

lemonade list

Orpheus-TTS-Local

A lightweight client for running Orpheus TTS locally using LM Studio API.

{Github Repo](https://github.com/isaiahbjork/orpheus-tts-local)

Features

🎧 High-quality Text-to-Speech using the Orpheus TTS model
💻 Completely local - no cloud API keys needed
🔊 Multiple voice options (tara, leah, jess, leo, dan, mia, zac, zoe)
💾 Save audio to WAV files

Quick Setup

Install LM Studio
Install the Orpheus TTS model (orpheus-3b-0.1-ft-q4_k_m.gguf) in LM Studio
Load the Orpheus model in LM Studio
Start the local server in LM Studio (default: http://127.0.0.1:1234)

Install dependencies:

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Run the script:

python gguf_orpheus.py --text "Hello, this is a test" --voice tara

Usage

python gguf_orpheus.py --text "Your text here" --voice tara --output "output.wav"

Options

--text: The text to convert to speech
--voice: The voice to use (default: tara)
--output: Output WAV file path (default: auto-generated filename)
--list-voices: Show available voices
--temperature: Temperature for generation (default: 0.6)
--top_p: Top-p sampling parameter (default: 0.9)
--repetition_penalty: Repetition penalty (default: 1.1)

Available Voices

tara - Best overall voice for general use (default)
leah
jess
leo
dan
mia
zac
zoe

Emotion

You can add emotion to the speech by adding the following tags:

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

License

Apache 2.0

Downloads last month: 6,629

GGUF

Model size

4B params

Architecture

llama

Hardware compatibility

4-bit

Model tree for isaiahbjork/orpheus-3b-0.1-ft-Q4_K_M-GGUF

Base model

meta-llama/Llama-3.2-3B-Instruct

Finetuned

canopylabs/orpheus-3b-0.1-pretrained

Finetuned

canopylabs/orpheus-3b-0.1-ft

Quantized

(31)

this model