Instructions to use pot99rta/DarkThink-DirectiveReasoner-12B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pot99rta/DarkThink-DirectiveReasoner-12B-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("pot99rta/DarkThink-DirectiveReasoner-12B-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use pot99rta/DarkThink-DirectiveReasoner-12B-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 pot99rta/DarkThink-DirectiveReasoner-12B-GGUF:Q4_0 # Run inference directly in the terminal: llama cli -hf pot99rta/DarkThink-DirectiveReasoner-12B-GGUF:Q4_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf pot99rta/DarkThink-DirectiveReasoner-12B-GGUF:Q4_0 # Run inference directly in the terminal: llama cli -hf pot99rta/DarkThink-DirectiveReasoner-12B-GGUF:Q4_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 pot99rta/DarkThink-DirectiveReasoner-12B-GGUF:Q4_0 # Run inference directly in the terminal: ./llama-cli -hf pot99rta/DarkThink-DirectiveReasoner-12B-GGUF:Q4_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 pot99rta/DarkThink-DirectiveReasoner-12B-GGUF:Q4_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf pot99rta/DarkThink-DirectiveReasoner-12B-GGUF:Q4_0
Use Docker
docker model run hf.co/pot99rta/DarkThink-DirectiveReasoner-12B-GGUF:Q4_0
- LM Studio
- Jan
- Ollama
How to use pot99rta/DarkThink-DirectiveReasoner-12B-GGUF with Ollama:
ollama run hf.co/pot99rta/DarkThink-DirectiveReasoner-12B-GGUF:Q4_0
- Unsloth Desktop
- Pi
How to use pot99rta/DarkThink-DirectiveReasoner-12B-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf pot99rta/DarkThink-DirectiveReasoner-12B-GGUF:Q4_0
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": "pot99rta/DarkThink-DirectiveReasoner-12B-GGUF:Q4_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use pot99rta/DarkThink-DirectiveReasoner-12B-GGUF with Docker Model Runner:
docker model run hf.co/pot99rta/DarkThink-DirectiveReasoner-12B-GGUF:Q4_0
- Lemonade
How to use pot99rta/DarkThink-DirectiveReasoner-12B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull pot99rta/DarkThink-DirectiveReasoner-12B-GGUF:Q4_0
Run and chat with the model
lemonade run user.DarkThink-DirectiveReasoner-12B-GGUF-Q4_0
List all available models
lemonade list
- Hermes Agent
How to use pot99rta/DarkThink-DirectiveReasoner-12B-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 pot99rta/DarkThink-DirectiveReasoner-12B-GGUF:Q4_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 pot99rta/DarkThink-DirectiveReasoner-12B-GGUF:Q4_0
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use pot99rta/DarkThink-DirectiveReasoner-12B-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf pot99rta/DarkThink-DirectiveReasoner-12B-GGUF:Q4_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 "pot99rta/DarkThink-DirectiveReasoner-12B-GGUF:Q4_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"
DarkThink-DirectiveReasoner-12B-GGUF
More Robust with all the Darkness added.
Models Merged:
1. ReadyArt/Omega-Darker_The-Final-Directive-12B
2. pot99rta/MagcarpMell-ThinkandReasoner-12B
Preset:
Use ChatML or Mistral
ChatML works better for reasoning due to Magicap and MagMell being ChatML for their base Models.
Just realized I've been spelling Magcap with 'Magcarp' this WHOLE time..
This model was converted to GGUF format from pot99rta/DarkThink-DirectiveReasoner-12B using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo pot99rta/DarkThink-DirectiveReasoner-12B-Q8_0-GGUF --hf-file darkthink-directivereasoner-12b-q8_0.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo pot99rta/DarkThink-DirectiveReasoner-12B-Q8_0-GGUF --hf-file darkthink-directivereasoner-12b-q8_0.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
git clone https://github.com/ggerganov/llama.cpp
Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
cd llama.cpp && LLAMA_CURL=1 make
Step 3: Run inference through the main binary.
./llama-cli --hf-repo pot99rta/DarkThink-DirectiveReasoner-12B-Q8_0-GGUF --hf-file darkthink-directivereasoner-12b-q8_0.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo pot99rta/DarkThink-DirectiveReasoner-12B-Q8_0-GGUF --hf-file darkthink-directivereasoner-12b-q8_0.gguf -c 2048
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Base model
pot99rta/DarkThink-DirectiveReasoner-12B