Instructions to use Rudi193/Kart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Rudi193/Kart with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Rudi193/Kart",
	filename="kart-unsloth.Q4_K_M.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use Rudi193/Kart with llama.cpp:

Install from brew

brew install llama.cpp
# 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

Install from WinGet (Windows)

winget install llama.cpp
# 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

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 Studio new

How to use Rudi193/Kart 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 Rudi193/Kart 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 Rudi193/Kart to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Rudi193/Kart to start chatting

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

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

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

Downloads last month: 1

GGUF

Model size

8B params

Architecture

qwen2

Hardware compatibility

4-bit

16-bit

Inference Providers NEW

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Model tree for Rudi193/Kart

Base model

Qwen/Qwen2.5-7B

Finetuned

Qwen/Qwen2.5-Coder-7B

Finetuned

Qwen/Qwen2.5-Coder-7B-Instruct

Finetuned

unsloth/Qwen2.5-Coder-7B-Instruct

Quantized

(14)

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