EngineeringWays: Circuit Analysis Reasoning Dataset (LoRA Ready) — Enterprise: Single Team

Skip the scraping, cleaning, and formatting. Start fine-tuning immediately.

The EngineeringWays Circuit Analysis Reasoning Dataset is a commercially viable, strictly deduplicated, and rigorously formatted JSONL dataset designed specifically for training Large Language Models (LLMs) in advanced STEM reasoning.

Built for fine-tuning models like Llama 3, Mistral, and DeepSeek, this dataset forces the AI to learn the underlying algebra and physics of electrical engineering rather than just memorizing answers.

Enterprise — Single Team License Scope

This specific tier is designed for individual project teams, AI labs, or specific departments within larger organizations.

• Commercial Rights: Fully cleared for commercial use. You can integrate the models you train into paid applications, SaaS platforms, APIs, or client work.

• No Revenue/Size Caps: Bypasses the $1M revenue and 10-employee limitations of the Standard tier.

• Team-Siloed: This license grants unrestricted access to a single designated business unit or product team within your company. (Note: If you require company-wide access across multiple global departments, please select the Enterprise — Global tier).

 View the full Master Dataset License Agreement here: [Click here]

What makes this dataset premium?

• Chain-of-Thought (<think> tags): Every problem includes an internal scratchpad/monologue where the AI breaks down the KVL/KCL equations, identifies supernodes/supermeshes, and self-corrects before outputting the final answer.
• Strict Textbook Formatting: All math and final answers are perfectly wrapped in industry-standard LaTeX ($...$ and $$...$$ ).
• Zero Hallucinations: Manually verified for algebraic and physical accuracy.
• Aggressively Deduplicated: Filtered down from raw generation to 592 perfectly unique, high-quality items. No exact copy-pastes, no low-quality or suspiciously short outputs.

Technical Specs:

• Format: .jsonl (JSON Lines) - Ready for immediate Hugging Face / LoRA pipeline ingestion.
• Row Count: 592 Unique Items
• Domain: Electrical Engineering, Circuit Analysis, Nodal/Mesh Analysis, Op-Amps, Thevenin Equivalents.
• Structure: Standard {"instruction": "...", "input": "...", "output": "<think>...</think>..."} format.

Try before you buy: Download a free 50-item sample on our Kaggle/Hugging Face/GitHub page!