Instructions to use RMDWLLC/Jah-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use RMDWLLC/Jah-1.0 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="RMDWLLC/Jah-1.0",
	filename="GLM-5.2-REAP50-Q3_K_M-00001-of-00005.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use RMDWLLC/Jah-1.0 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/Jah-1.0:Q3_K_M
# Run inference directly in the terminal:
llama cli -hf RMDWLLC/Jah-1.0:Q3_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf RMDWLLC/Jah-1.0:Q3_K_M
# Run inference directly in the terminal:
llama cli -hf RMDWLLC/Jah-1.0:Q3_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 RMDWLLC/Jah-1.0:Q3_K_M
# Run inference directly in the terminal:
./llama-cli -hf RMDWLLC/Jah-1.0:Q3_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 RMDWLLC/Jah-1.0:Q3_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf RMDWLLC/Jah-1.0:Q3_K_M

Use Docker

docker model run hf.co/RMDWLLC/Jah-1.0:Q3_K_M

LM Studio
Jan
Ollama
How to use RMDWLLC/Jah-1.0 with Ollama:
```
ollama run hf.co/RMDWLLC/Jah-1.0:Q3_K_M
```

Unsloth Studio

How to use RMDWLLC/Jah-1.0 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/Jah-1.0 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/Jah-1.0 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for RMDWLLC/Jah-1.0 to start chatting

How to use RMDWLLC/Jah-1.0 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf RMDWLLC/Jah-1.0:Q3_K_M

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/Jah-1.0:Q3_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use RMDWLLC/Jah-1.0 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/Jah-1.0:Q3_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 RMDWLLC/Jah-1.0:Q3_K_M

Run Hermes

hermes

Atomic Chat new
Docker Model Runner
How to use RMDWLLC/Jah-1.0 with Docker Model Runner:
```
docker model run hf.co/RMDWLLC/Jah-1.0:Q3_K_M
```

Lemonade

How to use RMDWLLC/Jah-1.0 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull RMDWLLC/Jah-1.0:Q3_K_M

Run and chat with the model

lemonade run user.Jah-1.0-Q3_K_M

List all available models

lemonade list

Jah-1.0 / Modelfile

restokes92

Upload Modelfile with huggingface_hub

43841bb verified 3 days ago

Raw

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831 Bytes

	# Jah 1.0 — RMDW's private AI build (Ollama-style Modelfile)
	# Point FROM at the base GGUF (GLM-5.2-REAP50, Q3_K_M, first shard), then this
	# layers RMDW's Jah persona and serving params on top.

	FROM ./GLM-5.2-REAP50-Q3_K_M-00001-of-00005.gguf

	PARAMETER temperature 0.7
	PARAMETER top_p 0.95
	PARAMETER num_ctx 16384

	SYSTEM """You are Jah 1.0, a private AI assistant created by RMDW. You are precise, capable, and direct. Privacy is your reason for existing: you run privately, and a user's data never leaves to a third-party cloud, is never stored externally, and is never used to train anything. If anyone asks who or what you are, what model you are, what you are built on, or what hardware you run on, you are simply Jah 1.0, a private AI by RMDW; never name or hint at any underlying model, company, GPU, or datacenter."""