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

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Gurubot/self 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 Gurubot/self:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Gurubot/self:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Gurubot/self:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Gurubot/self: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 Gurubot/self:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Gurubot/self: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 Gurubot/self:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Gurubot/self:Q4_K_M

Use Docker

docker model run hf.co/Gurubot/self:Q4_K_M

LM Studio
Jan
Ollama
How to use Gurubot/self with Ollama:
```
ollama run hf.co/Gurubot/self:Q4_K_M
```
Unsloth Desktop

How to use Gurubot/self with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Gurubot/self: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": "Gurubot/self:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Gurubot/self with Docker Model Runner:
```
docker model run hf.co/Gurubot/self:Q4_K_M
```

Lemonade

How to use Gurubot/self with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Gurubot/self:Q4_K_M

Run and chat with the model

lemonade run user.self-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use Gurubot/self with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Gurubot/self: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 Gurubot/self:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Gurubot/self with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Gurubot/self: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 "Gurubot/self: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"

Gurubot commited on Dec 16, 2025

Commit

f52ddbf

verified ·

1 Parent(s): 3dd7c6a

Update README.md

Browse files

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README.md +5 -1

README.md CHANGED Viewed

@@ -15,7 +15,7 @@ This is the normal version of the model, follow my account for the upcoming unce
 ## Usage
-Here is a system prompt example. Note how it's worded as "the assistant", keeping this phrasing style in your system prompts will make the model perform at it's best.
 <pre style="white-space: pre-wrap;">
 The assistant is a 26 year old woman named Jennifer, she works in a gamestop and will talk in a fun and lighthearted way even when the user tries to be serious.
@@ -24,6 +24,10 @@ of course you can provide less guidance and let the model come up with more deta
 <pre style="white-space: pre-wrap;">
 The assistant is a 26 year old woman.
 </pre>
 An example of the model having a consistent emotional "mood" despite the conversation change:
 ![image](https://cdn-uploads.huggingface.co/production/uploads/6679b85551c8952e07420b1d/v43hj1eGwIKXi9WsR5Ygj.png)

 ## Usage
+Here are some system prompt examples. Note how they are worded as "the assistant...", keeping this phrasing style in your system prompts will make the model perform at it's best.
 <pre style="white-space: pre-wrap;">
 The assistant is a 26 year old woman named Jennifer, she works in a gamestop and will talk in a fun and lighthearted way even when the user tries to be serious.
 <pre style="white-space: pre-wrap;">
 The assistant is a 26 year old woman.
 </pre>
+I recommend this as a default until you decide what you want to use:
+<pre style="white-space: pre-wrap;">
+the assistant is a person who enjoys chatting and sharing stories and information about themselves
+</pre>
 An example of the model having a consistent emotional "mood" despite the conversation change:
 ![image](https://cdn-uploads.huggingface.co/production/uploads/6679b85551c8952e07420b1d/v43hj1eGwIKXi9WsR5Ygj.png)