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 rhoahndur/retrosynthesis-qwen3-4b-gguf:Q4_K_M
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": "rhoahndur/retrosynthesis-qwen3-4b-gguf:Q4_K_M"
        }
      ]
    }
  }
}
Run Pi
# Start Pi in your project directory:
pi
Quick Links

Retrosynthesis Qwen3-4B GGUF

Q4_K_M quantized version of rhoahndur/retrosynthesis-qwen3-4b for CPU inference via llama.cpp.

Size: 2.5 GB Quantization: Q4_K_M

Usage with llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
    repo_id="rhoahndur/retrosynthesis-qwen3-4b-gguf",
    filename="retrosynthesis-qwen3-4b-Q4_K_M.gguf",
    n_ctx=512,
)
output = llm.create_chat_completion(
    messages=[
        {"role": "system", "content": "You are a retrosynthesis expert. Output ONLY reactant SMILES separated by dots."},
        {"role": "user", "content": "Predict the reactants for: CC(=O)Oc1ccccc1C(=O)O"}
    ],
    max_tokens=256,
    temperature=0.7,
)
print(output["choices"][0]["message"]["content"])

Demo

Retrosynthesis AI

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GGUF
Model size
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Architecture
qwen3
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