Instructions to use gggff123/lfmCodeEnhanced 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 gggff123/lfmCodeEnhanced 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 gggff123/lfmCodeEnhanced:Q4_K_M # Run inference directly in the terminal: llama cli -hf gggff123/lfmCodeEnhanced:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf gggff123/lfmCodeEnhanced:Q4_K_M # Run inference directly in the terminal: llama cli -hf gggff123/lfmCodeEnhanced: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 gggff123/lfmCodeEnhanced:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf gggff123/lfmCodeEnhanced:Q4_K_M
Use Docker
docker model run hf.co/gggff123/lfmCodeEnhanced:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use gggff123/lfmCodeEnhanced with Ollama:
ollama run hf.co/gggff123/lfmCodeEnhanced:Q4_K_M
- Unsloth Desktop
- Pi
How to use gggff123/lfmCodeEnhanced with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf gggff123/lfmCodeEnhanced: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": "gggff123/lfmCodeEnhanced:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use gggff123/lfmCodeEnhanced with Docker Model Runner:
docker model run hf.co/gggff123/lfmCodeEnhanced:Q4_K_M
- Lemonade
How to use gggff123/lfmCodeEnhanced with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull gggff123/lfmCodeEnhanced:Q4_K_M
Run and chat with the model
lemonade run user.lfmCodeEnhanced-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use gggff123/lfmCodeEnhanced with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf gggff123/lfmCodeEnhanced: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 gggff123/lfmCodeEnhanced:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use gggff123/lfmCodeEnhanced with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf gggff123/lfmCodeEnhanced: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 "gggff123/lfmCodeEnhanced: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 gggff123/lfmCodeEnhanced: direct link, hf CLI and curl.
- Browser
- Download file 2.52 kB
-
https://huggingface.co/gggff123/lfmCodeEnhanced/resolve/main/README.md
- Command line
-
hf download hf://gggff123/lfmCodeEnhanced/README.md
-
curl -L -o README.md https://huggingface.co/gggff123/lfmCodeEnhanced/resolve/main/README.md
2.52 kB
| license: mit | |
| language: | |
| - en | |
| base_model: | |
| - LiquidAI/LFM2.5-230M | |
| ## LFM 2.5 230m Code-Enhanced | |
| Lfm 2.5 230m code enhanced is a code-ish version of the previous lfm 2.5 230m (base) , this model however attempts to make the old model better at coding | |
| this uses the latest weight space programming paper along with deepseek v4.1 flash to manually change the model weights. | |
| <!DOCTYPE html> | |
| <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1"> | |
| <title>LFM CodeEnhanced AI</title> | |
| <style> | |
| * { box-sizing: border-box; } | |
| body { | |
| margin: 0; | |
| min-height: 100vh; | |
| display: grid; | |
| place-items: center; | |
| background: #080b14; | |
| font-family: Inter, Arial, sans-serif; | |
| } | |
| .logo { | |
| display: flex; | |
| align-items: center; | |
| gap: 18px; | |
| } | |
| svg { width: 100px; height: 100px; } | |
| .brand-name { | |
| font-size: 30px; | |
| font-weight: 850; | |
| letter-spacing: -1.5px; | |
| color: black; | |
| } | |
| .brand-name span { | |
| background: linear-gradient(100deg,#00e5ff,#9361ff); | |
| -webkit-background-clip: text; | |
| background-clip: text; | |
| color: transparent; | |
| } | |
| .tagline { | |
| margin-top: 7px; | |
| color: #8996b5; | |
| font-size: 10px; | |
| font-weight: 700; | |
| letter-spacing: 4px; | |
| } | |
| </style> | |
| </head> | |
| <body> | |
| <div class="logo"> | |
| <svg viewBox="0 0 100 100" fill="none"> | |
| <defs> | |
| <linearGradient id="g" x1="10" y1="10" x2="90" y2="90"> | |
| <stop stop-color="#00e5ff"/> | |
| <stop offset="1" stop-color="#9361ff"/> | |
| </linearGradient> | |
| </defs> | |
| <path d="M50 4 91 27V73L50 96 9 73V27L50 4Z" | |
| fill="#111a30" stroke="url(#g)" stroke-width="2.5"/> | |
| <path d="m35 33-15 17 15 17M65 33l15 17-15 17" | |
| stroke="url(#g)" stroke-width="5" | |
| stroke-linecap="round" stroke-linejoin="round"/> | |
| <path d="m50 23 6 21 21 6-21 6-6 21-6-21-21-6 21-6 6-21Z" | |
| fill="url(#g)"/> | |
| <circle cx="50" cy="50" r="5" fill="white"/> | |
| </svg> | |
| <div> | |
| <div class="brand-name">LFM <span>CodeEnhanced</span></div> | |
| <div class="tagline">AI · CODE · CREATE</div> | |
| </div> | |
| </div> | |
| </body> | |
| </html> | |
| Currently has 3 quantizations | |
| -- | |
| | Quantization | Quality | | |
| |----------------|--------| | |
| | BF16 | Highest quality <span style="background-color: #12CA12; color: black; padding: 2px 8px; border-radius: 10px; font-size: 12px; font-weight: bold;">Recommended</span> | |
| | Q4_KM | Mid Quality | | |
| | Q8 | Also good | | |
| --- | |
| This model was generated by deepseek V4.1 FLASH by changing model weights. | |
| All credits to <b>liquid-ai, deepseek & weight space programming research paper</b> | |
| --- |