Instructions to use prithivMLmods/Luna-f32-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Luna-f32-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="prithivMLmods/Luna-f32-GGUF") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("prithivMLmods/Luna-f32-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use prithivMLmods/Luna-f32-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 prithivMLmods/Luna-f32-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf prithivMLmods/Luna-f32-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf prithivMLmods/Luna-f32-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf prithivMLmods/Luna-f32-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 prithivMLmods/Luna-f32-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf prithivMLmods/Luna-f32-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 prithivMLmods/Luna-f32-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf prithivMLmods/Luna-f32-GGUF:Q4_K_M
Use Docker
docker model run hf.co/prithivMLmods/Luna-f32-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use prithivMLmods/Luna-f32-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "prithivMLmods/Luna-f32-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "prithivMLmods/Luna-f32-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/prithivMLmods/Luna-f32-GGUF:Q4_K_M
- SGLang
How to use prithivMLmods/Luna-f32-GGUF with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "prithivMLmods/Luna-f32-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "prithivMLmods/Luna-f32-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "prithivMLmods/Luna-f32-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "prithivMLmods/Luna-f32-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use prithivMLmods/Luna-f32-GGUF with Ollama:
ollama run hf.co/prithivMLmods/Luna-f32-GGUF:Q4_K_M
- Unsloth Desktop
- Pi
How to use prithivMLmods/Luna-f32-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf prithivMLmods/Luna-f32-GGUF:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "prithivMLmods/Luna-f32-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use prithivMLmods/Luna-f32-GGUF with Docker Model Runner:
docker model run hf.co/prithivMLmods/Luna-f32-GGUF:Q4_K_M
- Lemonade
How to use prithivMLmods/Luna-f32-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull prithivMLmods/Luna-f32-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Luna-f32-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use prithivMLmods/Luna-f32-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 prithivMLmods/Luna-f32-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 prithivMLmods/Luna-f32-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use prithivMLmods/Luna-f32-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf prithivMLmods/Luna-f32-GGUF:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "prithivMLmods/Luna-f32-GGUF:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Breaks once it hits Context Limit
It's a very intelligent model, useful for all sorts of things, and fast too.
But the moment it crosses that Context Limit, it breaks. It doesn't matter if it's set to 8192, 16384, or 32768—once it hits 100%, poof.
Forgot to mention I'm using the Q6_K version, but I really wish I knew why it breaks at Context Limit.
EDIT: Seems to be a Q6_K issue, F16 does not have the problem, but it's slow as crap. Is there any chance we can get an MXFP4 version of the model?
Further testing shows Q8_0 doesn't have the issue either, just Q6_K (and most likely below) also has the issue.
Once it spits out system, it just repeats it no matter what the [Current Input] is.
Contents of system:
You are a helpful assistant. You must never write for the user again.
You must only write dialog and narration, never explanations or apologies.
If you do not understand a request, you must ask clarifying questions.
Do not write for the user. Only respond as the character described.
Never write: "I'm sorry", "I see that you might be feeling...", "Let me know if this helps".
Only write what the character would say or do in that specific scenario.
Another thing I forgot to mention is that the model still refers to itself as 'Qwen', and has never referred to itself as 'Luna'.
I meet same issues but I set name model in system prompt it work fine . You can use the base model for testing it