Bienvenidos, Team SolarPulse
Rank #8 / 50JupyterHub URL
p3x9k.proxy.runpod.net
OpenRouter Key
sk-or-v1-a8f3…d92e
Dataset · HuggingFace
cleantechhub/datathon-2025
Task brief
Se les entrega un dataset de 10,000 registros de consumo energético de municipios de Latinoamérica — variables climáticas, datos demográficos y de política. Predigan el potencial de reducción de CO₂ (kg/año) alcanzable mediante transiciones a energía renovable.
Métrica: R² — más alto es mejor. Formato: CSV con columnas id, prediction. Límite: 10 envíos por día.
Your GPU Notebook
Online# Quick start — run this in your first cell import os, datasets, pandas as pd ds = datasets.load_dataset("cleantechhub/datathon-2025") df_train = ds["train"].to_pandas() df_test = ds["test"].to_pandas() import torch print(f"GPU: {torch.cuda.get_device_name(0)}")
T4
GPU model
16 GB
VRAM
100 GB
SSD storage
LLM API · OpenRouter
Cap $20.00Your API key · hard cap $20.00
sk-or-v1-a8f3c7b2e1d4f9a0c5b8e3d92e
from openai import OpenAI client = OpenAI(api_key="sk-or-v1-…", base_url="https://openrouter.ai/api/v1") resp = client.chat.completions.create( model="anthropic/claude-3-5-sonnet", messages=[{"role":"user", "content": f"CO₂ potential: {row}"}])
Probar el API en vivo
Sends one sample row to claude-3-5-sonnet and draws down your budget.
| Model | In / 1M | Out / 1M | Best for |
|---|---|---|---|
| claude-3-5-sonnet | $3.00 | $15.00 | Analysis, reasoning |
| gpt-4o | $2.50 | $10.00 | Code, structured output |
| gemini-pro-1.5 | $1.25 | $5.00 | Long context |
| llama-3.1-70b | $0.88 | $0.88 | Fast, budget |
| mistral-large | $2.00 | $6.00 | Multilingual |
Submit Your Solution
8 / 10 todayUpload predictions as CSV with columns id, prediction. Scoring runs automatically on a held-out set via Modal — results land on the leaderboard in ~3 min.
Drop your CSV here or click to browse
Max 50 MB · columns [id, prediction]
Submission history
| # | Time | Score (R²) | Status |
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Live Leaderboard
Updates 3 min
You · #8
| # | Team | Score (R²) | Subs |
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