Instructions to use steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF", filename="ultravox-v0_5-llama-3_1-8b.Q6_K_H.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H # Run inference directly in the terminal: llama-cli -hf steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H # Run inference directly in the terminal: llama-cli -hf steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H
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 steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H # Run inference directly in the terminal: ./llama-cli -hf steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H
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 steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H # Run inference directly in the terminal: ./build/bin/llama-cli -hf steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H
Use Docker
docker model run hf.co/steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H
- LM Studio
- Jan
- Ollama
How to use steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF with Ollama:
ollama run hf.co/steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H
- Unsloth Studio new
How to use steampunque/ultravox-v0_5-llama-3_1-8b-MP-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 steampunque/ultravox-v0_5-llama-3_1-8b-MP-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 steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF to start chatting
- Pi new
How to use steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H
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": "steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use steampunque/ultravox-v0_5-llama-3_1-8b-MP-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 steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H
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 steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H
Run Hermes
hermes
- Docker Model Runner
How to use steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF with Docker Model Runner:
docker model run hf.co/steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H
- Lemonade
How to use steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H
Run and chat with the model
lemonade run user.ultravox-v0_5-llama-3_1-8b-MP-GGUF-Q6_K_H
List all available models
lemonade list
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H# Run inference directly in the terminal:
llama-cli -hf steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_HUse 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 steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H# Run inference directly in the terminal:
./llama-cli -hf steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_HBuild 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 steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H# Run inference directly in the terminal:
./build/bin/llama-cli -hf steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_HUse Docker
docker model run hf.co/steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_Hmmproj GGUF ultravox-v0_5-llama-3_1-8b by fixie-ai
Original model: https://huggingface.co/fixie-ai/ultravox-v0_5-llama-3_1-8b
This is a F16 mmproj file intented to be used in conjunction with Llama-3.1-8B-Instruct. A high performance hybrid quant of Llama-3.1-8B-Instruct is available here: https://huggingface.co/steampunque/Llama-3.1-8B-Instruct-MP-GGUF
Usage:
Llama-3.1-8B-Instruct is made into an audio capable model using the fixie-ai audio multimedia projector tuned to work with it. This enables the model to input both audio (.mp3 and .wav files) and text inputs and generate text outputs. The mmproj file is made available in this repository and the hybrid quant model file is linked above and below. More information about running multimedia may be found in the docs in the mtmd readme in the tools directory of the llama.cpp source tree https://github.com/ggml-org/llama.cpp/blob/master/tools/mtmd/README.md.
Extensive testing show that as of 7/1/2025 this is the only useful/usable small audio model available for llama.cpp. The fixie 1b model based on Llama 3.2 1b and qwen omni 7b were both found to be extremely unreliable at the task of transcribing audio streams which is one of the most useful practical applications of an audio model. This model can transcribe audio streams extremely accurately as long as the audio is broken up into ~60s chunks maximum. ffmpeg can easily handle breaking up the audio into chunks and formatting it to a desired type and sample rate. Recommendeded sample rate is 16000, single audio channel, .wav format with 16 bits per sample with input audio broken up into 30s to 60s chunks for transcription. This config was tested to work well over a wide range of test audio clips ranging in duration up to 20m, with extremely accurate transcription found for 3 different tested voices.
The Deepseek R1 distill of Llama 3.1 8b is also compatible with this mmproj. A hybrid quant of this model is available here : https://huggingface.co/steampunque/Deepseek-R1-Distill-Llama-8B-Hybrid-GGUF
Note that a file ultravox-v0_5-llama-3_1-8b.Q6_K_H.gguf was made available in this repository, but its use is deprecated in favor of Llama-3.1-8B-Instruct naming to avoid confusion. Future ultravox hybrid quant releases will only provide the original model name in a separate model repository to avoid duplicating the exact file with a different name in the repository.
Benchmarks:
Audio benchmarks for the model will eventually be given here: https://huggingface.co/spaces/steampunque/benchlm
Download the file from below:
| Link | Type | Size/e9 B | Notes |
|---|---|---|---|
| Llama-3.1-8B-Instruct.Q6_K_H.gguf | Q6_K_H | 6e9 B | 0.6B smaller than Q6_K |
| ultravox-v0_5-llama-3_1-8b.mmproj.gguf | mmproj | 1.38e9 B | multimedia projector |
A discussion thread about the hybrid layer quant approach can be found here on the llama.cpp git repository:
- Downloads last month
- 23
6-bit
Model tree for steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF
Base model
fixie-ai/ultravox-v0_5-llama-3_1-8b
Install from brew
# Start a local OpenAI-compatible server with a web UI: llama-server -hf steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H# Run inference directly in the terminal: llama-cli -hf steampunque/ultravox-v0_5-llama-3_1-8b-MP-GGUF:Q6_K_H