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beakerduru
/
duru-e1

GGUF
gemma4
llama.cpp
unsloth
vision-language-model
conversational
Model card Files
xet
 Community
How to use from
Pi
Start the llama.cpp server 
# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf beakerduru/duru-e1:BF16
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": "beakerduru/duru-e1:BF16"
        }
      ]
    }
  }
}
Run Pi 
# Start Pi in your project directory:
pi
Quick Links

duru-e1 : GGUF

This model was finetuned and converted to GGUF format using Unsloth.

Example usage:

  • For text only LLMs: llama-cli -hf beakerduru/duru-e1 --jinja
  • For multimodal models: llama-mtmd-cli -hf beakerduru/duru-e1 --jinja

Available Model files:

  • gemma-4-e2b-it.Q4_K_M.gguf
  • gemma-4-e2b-it.BF16-mmproj.gguf

⚠️ Ollama Note for Vision Models

Important: Ollama currently does not support separate mmproj files for vision models.

To create an Ollama model from this vision model:

  1. Place the Modelfile in the same directory as the finetuned bf16 merged model
  2. Run: ollama create model_name -f ./Modelfile (Replace model_name with your desired name)

This will create a unified bf16 model that Ollama can use. This was trained 2x faster with Unsloth

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GGUF
Model size
5B params
Architecture
gemma4
Hardware compatibility
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