pkkidking/ix-coordination-tasks
0
IX Coordination Tasks
Instruction-tuning dataset for interconnection coordination in utility-scale solar and storage projects. Built from real Salesforce task logs (76K+ entries across 5,700+ projects) to train models on utility-specific workflows and rejection resolution.
Dataset Summary
- 35,005 instruction-response pairs (ShareGPT/ChatML format)
- 31,504 training / 3,501 validation (90/10 split)
- Covers 37+ utilities including Duke Energy, PG&E, Xcel, Consumers Energy, ComEd, AEP, PPL, and more
- Organized into 4 task categories
Categories
Data Format
Each example follows the ChatML/sharegpt format with system/user/assistant roles:
{
"messages": [
{"role": "system", "content": "You are an expert interconnection coordination assistant..."},
{"role": "user", "content": "Project: 1606MERE\nUtility: Duke Energy Progress NC\n..."},
{"role": "assistant", "content": "Rejection Analysis for 1606MERE | Duke Energy Progress NC\n..."}
]
}Intended Use
Fine-tuning small-to-medium LLMs (3B-8B) with QLoRA/LoRA for interconnection coordination assistance. The model learns to:
- Identify the correct utility-specific workflow
- Diagnose rejection causes from task log context
- Provide concrete resolution steps with follow-up timelines
- Reference utility portal requirements and submission procedures
Source Data
Built from the Interconnection Dash repository's Salesforce task log exports:
All-Task-Logs.csv(76,092 rows)All-Projects-All-Time.csv(utility name and state enrichment)
Retrieved May 5, 2026.
