functiongemma-finetuned-g1

FunctionGemma Robot Actions

A fine-tuned FunctionGemma 270M model that converts natural language into structured robot action and emotion function calls. Designed for real-time inference on edge devices like the NVIDIA Jetson AGX Thor.

Overview

This model takes a user's voice or text input and outputs two function calls:

• robot_action — a physical action for the robot to perform
• show_emotion — an emotion to display on the robot's avatar screen (Rive animations)

General conversation defaults to stand_still with a contextually appropriate emotion.

Example

Input:  "Can you shake hands with me?"
Output: robot_action(action_name="shake_hand") + show_emotion(emotion="happy")

Input:  "What is that?"
Output: robot_action(action_name="stand_still") + show_emotion(emotion="confused")

Input:  "I feel sad"
Output: robot_action(action_name="stand_still") + show_emotion(emotion="sad")

Supported Actions

Supported Emotions

Performance on NVIDIA Jetson AGX Thor

Benchmarked with constrained decoding (2 forward passes instead of 33 autoregressive steps):

Training Details

Quick Start

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model = AutoModelForCausalLM.from_pretrained(
    "OpenmindAGI/functiongemma-robot-actions",
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
tokenizer = AutoTokenizer.from_pretrained("OpenmindAGI/functiongemma-robot-actions")
model.eval()

Citation

@misc{openmindagi-functiongemma-robot-actions,
  title={FunctionGemma Robot Actions},
  author={OpenmindAGI},
  year={2025},
  url={https://huggingface.co/OpenmindAGI/functiongemma-robot-actions}
}