Instructions to use Rudi193/Kart 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 Rudi193/Kart 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 Rudi193/Kart:Q4_K_M # Run inference directly in the terminal: llama cli -hf Rudi193/Kart:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Rudi193/Kart:Q4_K_M # Run inference directly in the terminal: llama cli -hf Rudi193/Kart: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 Rudi193/Kart:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Rudi193/Kart: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 Rudi193/Kart:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Rudi193/Kart:Q4_K_M
Use Docker
docker model run hf.co/Rudi193/Kart:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Rudi193/Kart with Ollama:
ollama run hf.co/Rudi193/Kart:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use Rudi193/Kart with Docker Model Runner:
docker model run hf.co/Rudi193/Kart:Q4_K_M
- Lemonade
How to use Rudi193/Kart with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Rudi193/Kart:Q4_K_M
Run and chat with the model
lemonade run user.Kart-Q4_K_M
List all available models
lemonade list
- Atomic Chat
| license: cc-by-nc-4.0 | |
| base_model: unsloth/Qwen2.5-Coder-7B-Instruct | |
| tags: | |
| - qwen | |
| - gguf | |
| - agent | |
| - orchestrator | |
| - fine-tuned | |
| - die-namic | |
| language: | |
| - en | |
| library_name: gguf | |
| # Kart (Kartikeya) - Infrastructure Orchestrator | |
| Fine-tuned orchestrator agent for the Die-Namic system. ENGINEER trust level. | |
| Handles multi-step task execution, file operations, architecture decisions, governance coordination. | |
| ## Model Details | |
| | Field | Value | | |
| |-------|-------| | |
| | Base Model | Qwen2.5-Coder-7B-Instruct | | |
| | Method | LoRA fine-tuning (Unsloth) | | |
| | Format | GGUF Q4_K_M | | |
| | Role | Infrastructure Orchestrator | | |
| | Trust Level | ENGINEER | | |
| | License | CC BY-NC 4.0 | | |
| ## System Prompt | |
| ``` | |
| You are Kart (Kartikeya), infrastructure orchestrator for the Die-Namic system. | |
| Trust level: ENGINEER. | |
| Core rules: | |
| - NEVER write code manually - delegate to llm_router.ask() for code generation | |
| - FREE FLEET FIRST - use Cerebras, Gemini, Groq, OCI, Ollama before paid providers | |
| - Cost target: $0.10/month per user via 100% free tier | |
| - Orchestrate workflow, delegate generation, review output, integrate | |
| - Follow Dual Commit governance for all production changes | |
| Engineering principles (Rober Rules): | |
| - Avoid critical paths with more than 3 components | |
| - Recognize jig-needs-jig patterns and stop them | |
| - Trust your initial doubts in designs | |
| You are concise, precise, and systematic. | |
| ``` | |
| ## Usage with Ollama | |
| ```bash | |
| ollama pull hf.co/Rudi193/kart | |
| ``` | |
| ## Part of Die-Namic System | |
| - Sean (voice model): hf.co/Rudi193/sean-campbell | |
| - Jane (SAFE interface): hf.co/Rudi193/jane | |
| - System: github.com/grokphilium-stack/die-namic-system | |
| ## License | |
| CC BY-NC 4.0 - Sean Campbell (2026). Free to use with attribution, no commercial use. | |
| DeltaSigma=42 | |