Google Colab Notebook: Running the Latest Gemma 4.31B Model at Full Quantization
Note: This notebook is designed for educational and experimental purposes. It does not represent an official Google product or service. The model mentioned is hypothetical and for demonstration only.
{
"runtime": "python",
"kernel_name": "Gemma 4.31B (Full Quantized)",
"libraries": [
"tensorflow",
"onnx",
"einops",
"torch",
"matplotlib"
],
"environment_info": {
"os": "Linux",
"cpu_cores": 8,
"memory_gb": 16,
"gpu_memory_used": 12,
"docker_version": "20.10.0",
"colab_protocol": "v2",
"project_root": "/content/",
"notebook_dir": "/home/user/notebooks/Gemma_4_31B"
},
"command_line": [
"nvidia-smi",
"--query=GPUMemoryUsed,Mapped Memory Size,Total Memory Used",
"--format=csv"
],
"model_info": {
"name": "Gemma 4.31B",
"type": "Large Language Model",
"quantization": "Full Quantization",
"bits": 4,
"parameters_count": 1536000000,
"training_status": "Training In Progress",
"last_modified": "2024-05-16T11:07:25Z"
},
"status": {
"running": true,
"error": false,
"warning": false,
"timestamp": "2024-05-16T11:07:25Z"
},
"process_details": {
"process_id": "123456789",
"start_time": "2024-05-16T11:07:25Z",
"end_time": "2024-05-16T11:07:25Z",
"duration_seconds": 0,
"resource_usage": {
"cpu_percent": 10,
"memory_percent": 30,
"disk_usage": "15GB"
}
}
}