Instructions to use moolvylabs/Morphy-Math-1.5B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use moolvylabs/Morphy-Math-1.5B-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 moolvylabs/Morphy-Math-1.5B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf moolvylabs/Morphy-Math-1.5B-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 moolvylabs/Morphy-Math-1.5B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf moolvylabs/Morphy-Math-1.5B-GGUF:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf moolvylabs/Morphy-Math-1.5B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf moolvylabs/Morphy-Math-1.5B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/moolvylabs/Morphy-Math-1.5B-GGUF:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use moolvylabs/Morphy-Math-1.5B-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "moolvylabs/Morphy-Math-1.5B-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": "moolvylabs/Morphy-Math-1.5B-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/moolvylabs/Morphy-Math-1.5B-GGUF:Q4_K_M
- Ollama
How to use moolvylabs/Morphy-Math-1.5B-GGUF with Ollama:
ollama run hf.co/moolvylabs/Morphy-Math-1.5B-GGUF:Q4_K_M
- Unsloth Desktop
- Pi
How to use moolvylabs/Morphy-Math-1.5B-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf moolvylabs/Morphy-Math-1.5B-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": "moolvylabs/Morphy-Math-1.5B-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use moolvylabs/Morphy-Math-1.5B-GGUF with Docker Model Runner:
docker model run hf.co/moolvylabs/Morphy-Math-1.5B-GGUF:Q4_K_M
- Lemonade
How to use moolvylabs/Morphy-Math-1.5B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull moolvylabs/Morphy-Math-1.5B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Morphy-Math-1.5B-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use moolvylabs/Morphy-Math-1.5B-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 moolvylabs/Morphy-Math-1.5B-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 moolvylabs/Morphy-Math-1.5B-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use moolvylabs/Morphy-Math-1.5B-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf moolvylabs/Morphy-Math-1.5B-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 "moolvylabs/Morphy-Math-1.5B-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"
Download README.md from moolvylabs/Morphy-Math-1.5B-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 2.25 kB
-
https://huggingface.co/moolvylabs/Morphy-Math-1.5B-GGUF/resolve/main/README.md
- Command line
-
hf download hf://moolvylabs/Morphy-Math-1.5B-GGUF/README.md
-
curl -L -o README.md https://huggingface.co/moolvylabs/Morphy-Math-1.5B-GGUF/resolve/main/README.md
license: apache-2.0
base_model: qwen2.5-math-1.5b
tags:
- text-generation
- mathematics
- physics
- morphy
- moolvylabs
language:
- en
Morphy-Math-1.5B is the third model in the Morphy lineup developed by the Moolvylabs team. Unlike previous text-focused versions, this model has undergone selective, highly targeted fine-tuning on complex advanced academic datasets. It is fully optimized for exceptional performance in higher sciences while remaining lightweight enough to run locally on consumer-grade hardware.
✨ Strengths (What the model excels at)
- 🧮 Higher Mathematics & Calculus — outstanding performance in solving university-level limits, improper integrals, derivatives, and infinite series step-by-step using strict Chain of Thought (CoT).
- 📐 Linear Algebra & Differential Equations — effortlessly handles non-linear differential equations (such as Bernoulli equations), spectral theorems, matrix eigenvalues, and eigenvectors.
- ⚛️ Quantum Computing & Physics — natively understands advanced physics, Dirac bra-ket notations, Pauli operators, and complex quantum state transformations.
⚠️ Important Features and Limitations (Disclaimer)
Since this model is deployed across various quantization formats to support low-end hardware, please keep the following nuances in mind:
- 🔬 Model Quantization Impact: The full FP16 and Q8_0 versions retain near 100% of the model's complex reasoning logic. However, aggressive bit-compression variants (Q4_K_M / Q5_K_M) may occasionally exhibit minor logical degradation or index confusion on highly abstract, multi-variable academic equations (e.g., advanced tensor calculus).
- 🌐 Language Nuance: For maximum accuracy in complex symbolic formulas and advanced scientific notations, prompting the model in English is highly recommended.
🛠️ Technical Specifications
| Parameter | Value |
|---|---|
| Name | Morphy-Math-1.5B |
| Generation | Third model in the family |
| Base Model | Qwen2.5-Math-1.5B-Instruct |
| Data Type | Custom Higher Mathematics & Quantum Physics Paks |
| Purpose | Advanced Calculus / Tensor Analysis / Symbolic Reasoning |