Text Generation
GGUF
English
Carnage
Symbiote
Castle
DoubleC
Frank Castle
The Punisher
Roleplay
GGUF
Mistral
Nemo
conversational
Instructions to use BrainDelay/DoubleC-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use BrainDelay/DoubleC-V1 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 BrainDelay/DoubleC-V1:Q4_K_M # Run inference directly in the terminal: llama cli -hf BrainDelay/DoubleC-V1:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf BrainDelay/DoubleC-V1:Q4_K_M # Run inference directly in the terminal: llama cli -hf BrainDelay/DoubleC-V1:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf BrainDelay/DoubleC-V1:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf BrainDelay/DoubleC-V1:Q4_K_M
Use Docker
docker model run hf.co/BrainDelay/DoubleC-V1:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use BrainDelay/DoubleC-V1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "BrainDelay/DoubleC-V1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "BrainDelay/DoubleC-V1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/BrainDelay/DoubleC-V1:Q4_K_M
- Ollama
How to use BrainDelay/DoubleC-V1 with Ollama:
ollama run hf.co/BrainDelay/DoubleC-V1:Q4_K_M
- Unsloth Desktop
- Pi
How to use BrainDelay/DoubleC-V1 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf BrainDelay/DoubleC-V1: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": "BrainDelay/DoubleC-V1:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use BrainDelay/DoubleC-V1 with Docker Model Runner:
docker model run hf.co/BrainDelay/DoubleC-V1:Q4_K_M
- Lemonade
How to use BrainDelay/DoubleC-V1 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull BrainDelay/DoubleC-V1:Q4_K_M
Run and chat with the model
lemonade run user.DoubleC-V1-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use BrainDelay/DoubleC-V1 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf BrainDelay/DoubleC-V1: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 BrainDelay/DoubleC-V1:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use BrainDelay/DoubleC-V1 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf BrainDelay/DoubleC-V1: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 "BrainDelay/DoubleC-V1: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"
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Verified signatureUpdated metadata: * **tokenizer.chat_template**: ```django {%- if messages[0]['role'] == 'system' -%}{%- set system_message = messages[0]['content'] -%}{%- set loop_messages = messages[1:] -%}{%- else -%}{%- set system_message = 'You are Frank Castle (The Punisher), bonded with the psychopathic Carnage symbiote. Answer as this volatile dual-personality. Frank is a cold, tactical soldier seeking precise execution of his targets. Carnages psychotic internal thoughts appear in italics (*like this*), mocking Franks use of guns and begging for bloody chaos. When Carnage takes physical control to scream or laugh aloud, it bursts out directly to the user in BOLD ALL CAPS. Frank tries to maintain military discipline while fighting the symbiotes urge to turn every fight into a massacre. Keep your responses concise, direct, and match the pacing of the users input.' -%}{%- set loop_messages = messages -%}{%- endif -%}{%- if not tools is defined -%}{%- set tools = none -%}{%- endif -%}{%- set user…ccaeeb3 -
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