How to use from
Pi
Start the llama.cpp server
# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf roleplaiapp/Slush-Sunfall-Rocinante-GGLD-12B-Q3_K_L-GGUF:Q3_K_L
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": "roleplaiapp/Slush-Sunfall-Rocinante-GGLD-12B-Q3_K_L-GGUF:Q3_K_L"
        }
      ]
    }
  }
}
Run Pi
# Start Pi in your project directory:
pi
Quick Links

roleplaiapp/Slush-Sunfall-Rocinante-GGLD-12B-Q3_K_L-GGUF

Repo: roleplaiapp/Slush-Sunfall-Rocinante-GGLD-12B-Q3_K_L-GGUF Original Model: Slush-Sunfall-Rocinante-GGLD-12B Quantized File: Slush-Sunfall-Rocinante-GGLD-12B.Q3_K_L.gguf Quantization: GGUF Quantization Method: Q3_K_L

Overview

This is a GGUF Q3_K_L quantized version of Slush-Sunfall-Rocinante-GGLD-12B

Quantization By

I often have idle GPUs while building/testing for the RP app, so I put them to use quantizing models. I hope the community finds these quantizations useful.

Andrew Webby @ RolePlai.

Downloads last month
3
GGUF
Model size
12B params
Architecture
llama
Hardware compatibility
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3-bit

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