| --- |
| license: agpl-3.0 |
| tags: |
| - smoltrace |
| - smolagents |
| - evaluation |
| - benchmark |
| - llm |
| - agents |
| --- |
| |
| <div align="center"> |
| <img src="https://raw.githubusercontent.com/Mandark-droid/SMOLTRACE/main/.github/images/Logo.png" alt="SMOLTRACE Logo" width="400"/> |
|
|
| <h3>Tiny Agents. Total Visibility.</h3> |
|
|
| <p> |
| <a href="https://github.com/Mandark-droid/SMOLTRACE"><img src="https://img.shields.io/badge/GitHub-SMOLTRACE-blue?logo=github" alt="GitHub"></a> |
| <a href="https://pypi.org/project/smoltrace/"><img src="https://img.shields.io/pypi/v/smoltrace?color=green" alt="PyPI"></a> |
| <a href="https://github.com/Mandark-droid/SMOLTRACE#readme"><img src="https://img.shields.io/badge/docs-readme-orange" alt="Documentation"></a> |
| </p> |
| </div> |
| |
| --- |
|
|
|
|
| # SMOLTRACE GPU & Environmental Metrics |
|
|
| This dataset contains time-series GPU metrics and environmental impact data from a SMOLTRACE benchmark run. |
|
|
| ## Dataset Information |
|
|
| | Field | Value | |
| |-------|-------| |
| | **Model** | `allenai/Olmo-3-7B-Instruct` | |
| | **Run ID** | `87b74ff3-30b1-4410-aa10-6a785496849a` | |
| | **Total Samples** | 84 | |
| | **Generated** | 2025-11-26 10:47:42 UTC | |
| | **GPU Metrics** | Available | |
|
|
| ## Schema |
|
|
| | Column | Type | Description | |
| |--------|------|-------------| |
| | `run_id` | string | Unique run identifier | |
| | `timestamp` | string | ISO timestamp of measurement | |
| | `timestamp_unix_nano` | string | Unix nanosecond timestamp | |
| | `service_name` | string | Service identifier | |
| | `gpu_id` | string | GPU device ID | |
| | `gpu_name` | string | GPU model name | |
| | `gpu_utilization_percent` | float | GPU compute utilization (0-100%) | |
| | `gpu_memory_used_mib` | float | GPU memory used (MiB) | |
| | `gpu_memory_total_mib` | float | Total GPU memory (MiB) | |
| | `gpu_temperature_celsius` | float | GPU temperature (°C) | |
| | `gpu_power_watts` | float | GPU power consumption (W) | |
| | `co2_emissions_gco2e` | float | Cumulative CO2 emissions (gCO2e) | |
| | `power_cost_usd` | float | Cumulative power cost (USD) | |
|
|
| ## Environmental Impact |
|
|
| SMOLTRACE tracks environmental metrics to help you understand the carbon footprint of your AI workloads: |
|
|
| - **CO2 Emissions**: Calculated based on GPU power consumption and regional carbon intensity |
| - **Power Cost**: Estimated electricity cost based on configurable rates |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| import pandas as pd |
| |
| # Load metrics |
| ds = load_dataset("YOUR_USERNAME/smoltrace-metrics-TIMESTAMP") |
| |
| # Convert to DataFrame for analysis |
| df = pd.DataFrame(ds['train']) |
| |
| # Plot GPU utilization over time |
| import matplotlib.pyplot as plt |
| plt.plot(df['timestamp'], df['gpu_utilization_percent']) |
| plt.xlabel('Time') |
| plt.ylabel('GPU Utilization (%)') |
| plt.title('GPU Utilization During Evaluation') |
| plt.show() |
| |
| # Get total environmental impact |
| total_co2 = df['co2_emissions_gco2e'].max() |
| total_cost = df['power_cost_usd'].max() |
| print(f"Total CO2: {total_co2:.4f} gCO2e") |
| print(f"Total Cost: ${total_cost:.6f}") |
| ``` |
|
|
| ## Related Datasets |
|
|
| This evaluation run also generated: |
| - **Results Dataset**: Pass/fail outcomes for each test case |
| - **Traces Dataset**: Detailed OpenTelemetry execution traces |
| - **Leaderboard**: Aggregated metrics for model comparison |
|
|
| --- |
|
|
| ## About SMOLTRACE |
|
|
| **SMOLTRACE** is a comprehensive benchmarking and evaluation framework for [Smolagents](https://huggingface.co/docs/smolagents) - HuggingFace's lightweight agent library. |
|
|
| ### Key Features |
| - Automated agent evaluation with customizable test cases |
| - OpenTelemetry-based tracing for detailed execution insights |
| - GPU metrics collection (utilization, memory, temperature, power) |
| - CO2 emissions and power cost tracking |
| - Leaderboard aggregation and comparison |
|
|
| ### Quick Links |
| - [GitHub Repository](https://github.com/Mandark-droid/SMOLTRACE) |
| - [PyPI Package](https://pypi.org/project/smoltrace/) |
| - [Documentation](https://github.com/Mandark-droid/SMOLTRACE#readme) |
| - [Report Issues](https://github.com/Mandark-droid/SMOLTRACE/issues) |
|
|
| ### Installation |
|
|
| ```bash |
| pip install smoltrace |
| ``` |
|
|
| ### Citation |
|
|
| If you use SMOLTRACE in your research, please cite: |
|
|
| ```bibtex |
| @software{smoltrace, |
| title = {SMOLTRACE: Benchmarking Framework for Smolagents}, |
| author = {Thakkar, Kshitij}, |
| url = {https://github.com/Mandark-droid/SMOLTRACE}, |
| year = {2025} |
| } |
| ``` |
|
|
| --- |
|
|
| <div align="center"> |
| <sub>Generated by <a href="https://github.com/Mandark-droid/SMOLTRACE">SMOLTRACE</a></sub> |
| </div> |
|
|
