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README.md

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+---
+license: gemma
+base_model: google/functiongemma-270m-it
+library_name: llama.cpp
+tags:
+  - gguf
+  - gemma3
+  - function-calling
+  - tool-use
+  - tiny
+  - local
+  - cpu
+language:
+  - pt
+  - en
+---
+
+# Gargantua Pi (270M)
+
+Gargantua Pi is the tiniest model of the [openTARS](https://project-opentars.github.io/OpenTARS/) assistant. It is built for small boards and low-power machines: Raspberry Pi, Orange Pi and any computer without a graphics card. At about 300 MB it loads in a moment and answers on the CPU.
+
+It does four things well: run a terminal command, search the web, remember a fact, and forget one. It answers in Portuguese and English and politely says so when you ask for something it cannot do, such as looking at the screen.
+
+- **Base:** FunctionGemma 270M, fine-tuned by the openTARS project on its own tool-use data (4 tools: `execute_terminal`, `search_web`, `remember`, `forget`).
+- **File:** `gargantua-1.2-pi-functiongemma-270m-Q8_0.gguf` (0.3 GB).
+- **Runs with:** llama.cpp and Ollama (the `functiongemma` renderer and parser are built in).
+- **License:** Gemma Terms of Use, inherited from the base model. Anyone who redistributes it must pass those terms on.
+
+## Use
+
+With Ollama, create the model from the downloaded file:
+
+```bash
+printf 'FROM ./gargantua-1.2-pi-functiongemma-270m-Q8_0.gguf\nRENDERER functiongemma\nPARSER functiongemma\nPARAMETER temperature 0.1\n' > Modelfile
+ollama create gargantua-pi -f Modelfile
+ollama run gargantua-pi "how much free memory is there?"
+```
+
+Pass the four tools in the request so it can call them. The openTARS app does this for you.
+
+## Measured result
+
+On our own 39-request check of the first move (pick the right tool, or none) it gets 31 of 39 right. This is our own test, not a public benchmark.
+
+## Checksum
+
+SHA-256 of the GGUF: `f921e2370833585eda692d4878f9ba50899bdce18b57dc10d0300f8a66f5ac60`