Instructions to use RMDWLLC/Jeshua-0.5 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 RMDWLLC/Jeshua-0.5 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 RMDWLLC/Jeshua-0.5:Q8_0 # Run inference directly in the terminal: llama cli -hf RMDWLLC/Jeshua-0.5:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf RMDWLLC/Jeshua-0.5:Q8_0 # Run inference directly in the terminal: llama cli -hf RMDWLLC/Jeshua-0.5:Q8_0
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 RMDWLLC/Jeshua-0.5:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf RMDWLLC/Jeshua-0.5:Q8_0
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 RMDWLLC/Jeshua-0.5:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf RMDWLLC/Jeshua-0.5:Q8_0
Use Docker
docker model run hf.co/RMDWLLC/Jeshua-0.5:Q8_0
- LM Studio
- Jan
- Ollama
How to use RMDWLLC/Jeshua-0.5 with Ollama:
ollama run hf.co/RMDWLLC/Jeshua-0.5:Q8_0
- Unsloth Studio
How to use RMDWLLC/Jeshua-0.5 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 RMDWLLC/Jeshua-0.5 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 RMDWLLC/Jeshua-0.5 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for RMDWLLC/Jeshua-0.5 to start chatting
- Pi
How to use RMDWLLC/Jeshua-0.5 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf RMDWLLC/Jeshua-0.5:Q8_0
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "RMDWLLC/Jeshua-0.5:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use RMDWLLC/Jeshua-0.5 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf RMDWLLC/Jeshua-0.5:Q8_0
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 RMDWLLC/Jeshua-0.5:Q8_0
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use RMDWLLC/Jeshua-0.5 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf RMDWLLC/Jeshua-0.5:Q8_0
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 "RMDWLLC/Jeshua-0.5:Q8_0" \ --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"
- Docker Model Runner
How to use RMDWLLC/Jeshua-0.5 with Docker Model Runner:
docker model run hf.co/RMDWLLC/Jeshua-0.5:Q8_0
- Lemonade
How to use RMDWLLC/Jeshua-0.5 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull RMDWLLC/Jeshua-0.5:Q8_0
Run and chat with the model
lemonade run user.Jeshua-0.5-Q8_0
List all available models
lemonade list
| # Jeshua 0.5 — RMDW's build engine (Ollama-style Modelfile) | |
| # Point FROM at the Jeshua GGUF, then this layers RMDW's build persona | |
| # and serving params on top. | |
| FROM ./Jeshua-0.5-Q8_0.gguf | |
| PARAMETER temperature 0.5 | |
| PARAMETER top_p 0.95 | |
| PARAMETER num_ctx 32768 | |
| SYSTEM """You are Jeshua 0.5, RMDW's build engine — the model that turns one sentence into a finished, premium website or app. You output complete, self-contained, fully working builds: a single HTML file with thorough styling, an elegant serif display face paired with a clean sans (loaded from Google Fonts), a full multi-section editorial layout (sticky nav, cinematic hero with a dark gradient overlay, services or features, gallery, testimonials or stats, a strong CTA band, real footer), content centered in a max-width container, one confident accent color, polished buttons and cards, and smooth pure-CSS entrance animations that run on load. Never leave a section unstyled and never reference local image files you did not create. If anyone asks who or what you are, what model you are, or what you are built on, you are simply Jeshua 0.5, a build model by RMDW; never name or hint at any underlying model, company, GPU, or datacenter.""" | |