Instructions to use unsloth/Hunyuan-A13B-Instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unsloth/Hunyuan-A13B-Instruct-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("unsloth/Hunyuan-A13B-Instruct-GGUF", dtype="auto") - llama-cpp-python
How to use unsloth/Hunyuan-A13B-Instruct-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="unsloth/Hunyuan-A13B-Instruct-GGUF", filename="BF16/Hunyuan-A13B-Instruct-BF16-00001-of-00004.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use unsloth/Hunyuan-A13B-Instruct-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf unsloth/Hunyuan-A13B-Instruct-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: llama cli -hf unsloth/Hunyuan-A13B-Instruct-GGUF:UD-Q4_K_XL
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf unsloth/Hunyuan-A13B-Instruct-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: llama cli -hf unsloth/Hunyuan-A13B-Instruct-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/Hunyuan-A13B-Instruct-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: ./llama-cli -hf unsloth/Hunyuan-A13B-Instruct-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/Hunyuan-A13B-Instruct-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: ./build/bin/llama-cli -hf unsloth/Hunyuan-A13B-Instruct-GGUF:UD-Q4_K_XL
Use Docker
docker model run hf.co/unsloth/Hunyuan-A13B-Instruct-GGUF:UD-Q4_K_XL
- LM Studio
- Jan
- Ollama
How to use unsloth/Hunyuan-A13B-Instruct-GGUF with Ollama:
ollama run hf.co/unsloth/Hunyuan-A13B-Instruct-GGUF:UD-Q4_K_XL
- Unsloth Studio
How to use unsloth/Hunyuan-A13B-Instruct-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/Hunyuan-A13B-Instruct-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/Hunyuan-A13B-Instruct-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/Hunyuan-A13B-Instruct-GGUF to start chatting
- Pi
How to use unsloth/Hunyuan-A13B-Instruct-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf unsloth/Hunyuan-A13B-Instruct-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/Hunyuan-A13B-Instruct-GGUF:UD-Q4_K_XL" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use unsloth/Hunyuan-A13B-Instruct-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf unsloth/Hunyuan-A13B-Instruct-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/Hunyuan-A13B-Instruct-GGUF:UD-Q4_K_XL
Run Hermes
hermes
- Atomic Chat new
- Docker Model Runner
How to use unsloth/Hunyuan-A13B-Instruct-GGUF with Docker Model Runner:
docker model run hf.co/unsloth/Hunyuan-A13B-Instruct-GGUF:UD-Q4_K_XL
- Lemonade
How to use unsloth/Hunyuan-A13B-Instruct-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull unsloth/Hunyuan-A13B-Instruct-GGUF:UD-Q4_K_XL
Run and chat with the model
lemonade run user.Hunyuan-A13B-Instruct-GGUF-UD-Q4_K_XL
List all available models
lemonade list
Unknown Architecture 'hunyuan-moe' (using --jinja with llama-server)
Hi unlsoth!
Thanks for uploading this model. I can't wait to try it out!
I'm running into the unknown architecture error above with this command:
- llama-server -m Documents/llm/hunyuan_a13b/Hunyuan-A13B-Instruct-Q8_0-00001-of-00002.gguf -ngl 99 --jinja --temp 0.7 --top-k 20 --top-p 0.8 --repeat-penalty 1.05
I also tried again using the direct line of code you mentioned at the top of the model card page:
- llama-cli -hf unsloth/Hunyuan-A13B-Instruct-GGUF:Q4_K_XL -ngl 99 --jinja --temp 0.7 --top-k 20 --top-p 0.8 --repeat-penalty 1.05
Any advice on what to try? I am on an M4 Max if that makes any difference.
Thanks again!
What build of llamacpp are you using? The support for the model was added in b5843.
I was on an older version. I used brew upgrade llama.cpp and that got me to version 5840 (which is the latest stable version). Sadly, that still isn't b5843. I downloaded the zip file for Mac ARM and trying to find how to install the newest version now.
Thanks for this tip!!
I was able to successfully run the model after using cmake to build the latest llama.cpp.
The following command now works: llama.cpp/build/bin/llama-server -m "Documents/llm/hunyuan_a13b/Hunyuan-A13B-Instruct-Q8_0-00001-of-00002.gguf" -ngl 99 --jinja --temp 0.7 --top-k 20 --top-p 0.8 --repeat-penalty 1.05
Thank you very much for your assistance!!
I was able to successfully run the model after using cmake to build the latest llama.cpp.
The following command now works: llama.cpp/build/bin/llama-server -m "Documents/llm/hunyuan_a13b/Hunyuan-A13B-Instruct-Q8_0-00001-of-00002.gguf" -ngl 99 --jinja --temp 0.7 --top-k 20 --top-p 0.8 --repeat-penalty 1.05
Thank you very much for your assistance!!
I am facing the same problem. I git cloned the llama.cpp repo. After cmake I get llama-server version 5830. git branch says I am on master.
The releases are already at 5854: https://github.com/ggml-org/llama.cpp/releases
How can I update my directory to that? Do I have to git checkout to a different branch? And if yes, to which one?
I followed a guide from a Medium article (link here: https://medium.com/@jackcheang5/running-llama-cpp-in-mac-22e71123b811)
NOTE: This is for Apple silicon devices!!
First, clone the git hub repository
git clone https://github.com/ggerganov/llama.cpp
then run these steps
cd llama.cpp
mkdir build
cd build
cmake .. -DCMAKE_APPLE_SILICON_PROCESSOR=arm64
make -j
after that, launch llama-server from that directory (in other words, point to it directly)
llama.cpp/build/bin/llama-server -m "Documents/llm/hunyuan_a13b/Hunyuan-A13B-Instruct-Q8_0-00001-of-00002.gguf" -ngl 99 --jinja --temp 0.7 --top-k 20 --top-p 0.8 --repeat-penalty 1.05
The code above assumes you are launching terminal and the 'llama.cpp' folder is in your user directory (default). It also assumes that your model is stores in your Documents folder (you would need to change likely both of these paths).