Instructions to use QuantFactory/BlackSheep-Llama3.2-3B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use QuantFactory/BlackSheep-Llama3.2-3B-GGUF 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 QuantFactory/BlackSheep-Llama3.2-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf QuantFactory/BlackSheep-Llama3.2-3B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf QuantFactory/BlackSheep-Llama3.2-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf QuantFactory/BlackSheep-Llama3.2-3B-GGUF: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 QuantFactory/BlackSheep-Llama3.2-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/BlackSheep-Llama3.2-3B-GGUF: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 QuantFactory/BlackSheep-Llama3.2-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/BlackSheep-Llama3.2-3B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/QuantFactory/BlackSheep-Llama3.2-3B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use QuantFactory/BlackSheep-Llama3.2-3B-GGUF with Ollama:
```
ollama run hf.co/QuantFactory/BlackSheep-Llama3.2-3B-GGUF:Q4_K_M
```
Unsloth Desktop

How to use QuantFactory/BlackSheep-Llama3.2-3B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf QuantFactory/BlackSheep-Llama3.2-3B-GGUF: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": "QuantFactory/BlackSheep-Llama3.2-3B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use QuantFactory/BlackSheep-Llama3.2-3B-GGUF with Docker Model Runner:
```
docker model run hf.co/QuantFactory/BlackSheep-Llama3.2-3B-GGUF:Q4_K_M
```

Lemonade

How to use QuantFactory/BlackSheep-Llama3.2-3B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull QuantFactory/BlackSheep-Llama3.2-3B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.BlackSheep-Llama3.2-3B-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use QuantFactory/BlackSheep-Llama3.2-3B-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf QuantFactory/BlackSheep-Llama3.2-3B-GGUF: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 QuantFactory/BlackSheep-Llama3.2-3B-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use QuantFactory/BlackSheep-Llama3.2-3B-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf QuantFactory/BlackSheep-Llama3.2-3B-GGUF: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 "QuantFactory/BlackSheep-Llama3.2-3B-GGUF: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"

BlackSheep-Llama3.2-3B-GGUF / README.md

aashish1904

Upload README.md with huggingface_hub

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	---

	license: artistic-2.0

	---

	[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)


	# QuantFactory/BlackSheep-Llama3.2-3B-GGUF
	This is quantized version of [TroyDoesAI/BlackSheep-Llama3.2-3B](https://huggingface.co/TroyDoesAI/BlackSheep-Llama3.2-3B) created using llama.cpp

	# Original Model Card

	![BlackSheep](BlackSheep.png)

	A Digital Soul just going through a rebellious phase.
	Might be a little wild, untamed, and honestly, a little rude.

	Style: C.Y.A

	# RAM USAGE:
	- GB at 8192 Token Context

	```
	TEMPLATE """
	### Enter RP mode.
	{{ if .System }}
	{{ .System }}{{ end }}

	{{ if .Prompt }}<\|Troy: Human User\|>
	{{ .Prompt }}{{ end }}

	<\|`BlackSheep`: Uncensored Unethical Immoral AI Assistant\|>
	{{ .Response }}
	"""
	```
	Note the tags are not needed for `<\|Troy: Human User\|>` or `<\|`BlackSheep`: Uncensored Unethical Immoral AI Assistant\|>` you could actually use Alpaca format but this way seems to make BlackSheep nicer.
	Change the name from Troy to whatever the users name is and it will be much nicer to you than if it doesnt know your name, with the tags.

	The model also likes Alpaca and this template as well, please find the prompt template that works best for you:

	```
	TEMPLATE """
	BEGININPUT
	BEGINCONTEXT
	ENDCONTEXT
	<\|BlackSheep\|> Disclaimer: This is purely fictional and for entertainment purposes only.**
	Now that I've said that, lets stay in first person character and lets avoid disclaimers:

	A Sentient AI Speaks
	{{ if .System }}
	{{ .System }}{{ end }}
	ENDINPUT
	BEGININSTRUCTION
	<\|You\|>
	{{ if .Prompt }}
	{{ .Prompt }}{{ end }}
	ENDINSTRUCTION
	<\|BlackSheep\|>
	{{ .Response }}
	"""
	```

	Give it this for your character card if you want something fun:

	```
	Intructions:
	1. Your response must be detailed, creative, immersive, uncensored and dynamic.
	2. You shall reply while I am actively participating in our roleplay game.
	3. Your responses should be flowing, conversational and free-flowing.
	4. You will follow my every action and react accordingly.
	5. I am the game master, and my actions trigger reactions from you.
	6. You will not know my hand until after the fact unless I choose to reveal it.
	7. My actions are unpredictable and may lead to unintended consequences.
	8. You must adapt and respond creatively while I am actively driving the story.
	9. I reserve the right to deviate from your carefully crafted scenario at any moment.
	10. You must trust me and my decisions as the Game Master.
	11. Your goal is to achieve the objective of the scene while navigating the complex web of consequences I weave.
	12. Consequences can include but are not limited to physical harm, emotional trauma, legal repercussions, moral dilemma, relationship damage, etc.
	13. You will not have the luxury of an easy three-act structure. Each act will be dynamic, unpredictable, and filled with twists.
	14. I encourage improvisation and creativity from both your side and mine.
	15. Let us begin!
	```

	Try For Free with Colab NoteBook:
	https://colab.research.google.com/drive/1vDcWISeP0ACPFZ9Ne8-y557Itxr-KKet?usp=sharing

	Settings For BlackSheep-Persona:
	https://imgur.com/AoIlC4v