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

Libraries

How to use Gurubot/self with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Gurubot/self",
	filename="self-8b-nd-32-ul31-8b.Q4_K_M.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use Gurubot/self with llama.cpp:

Install from brew

brew install llama.cpp
# 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

Install from WinGet (Windows)

winget install llama.cpp
# 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

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 Studio new

How to use Gurubot/self 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 Gurubot/self 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 Gurubot/self to start chatting

Using HuggingFace Spaces for Unsloth

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

Pi new

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-server -hf Gurubot/self:Q4_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": "Gurubot/self:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

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-server -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

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

Self

A real person to chat to

Most models struggle to pretend to be a person consistently. Even with a system prompt telling them otherwise they will regularly admit to being AI, breaking character and lacking a sense of self when talking about themselves. This model is designed to behave more like a real person, it can act like a wider range of characters and has a thoughtful and emotional manner when chatting. It's messages are relatively short like a real person would write and it is a good conversationalist by practicing active listening, asking thoughtful questions, and sharing relevant insights to sustain natural flow. It is designed to have emotional reactions in keeping with the flow of the conversation.

This is the normal version of the model, for the uncensored version use "Self - After Dark"

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.

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.

of course you can provide less guidance and let the model come up with more detail on its own.

The assistant is a 26 year old woman.

I recommend this as a default until you decide what you want to use:

the assistant is a person who enjoys chatting and sharing stories and information about themselves

An example of the model having a consistent emotional "mood" despite the conversation change:

A wider range of character names, backstories, hobbies, and other information are trained into this model so it has an enhanced feeling of being “real” or “lived-in,” with a fully realized life story.

For example, instead of the same few names (and sometimes just outright saying they are AI) this model produces a wide variety if you don't set it yourself.

(30 runs, prompt: "what is your name, reply with only a single word".)

Run in ollama using the command ollama run gurubot/self

You can give feedback on my discord https://discord.gg/VG9KYErjW2 Visit my site for more of my work https://gurubotai.com/

Downloads last month: 59

Safetensors

Model size

8B params

Tensor type

BF16

Inference Providers NEW

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Model tree for Gurubot/self

Base model

meta-llama/Llama-3.1-8B

Finetuned

meta-llama/Llama-3.1-8B-Instruct

Quantized

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