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| Pass | Dataset | Examples | Best Val Loss |
|---|---|---|---|
| v2 domain | MetaMathQA, Open-Platypus, OpenHermes STEM, ArXiv QA, SciQ, WikiText, WikiQA, CAMEL Physics/Math, CodeAlpaca, Finance | ~56K | 0.617 |
| CoT reasoning | nvidia/OpenMathReasoning, Open-Platypus CoT, MetaMathQA CoT, handcrafted aerospace | ~11K | 0.439 |
| Precision | Handcrafted aerospace/thermo — correct R=8314/M derivation (never R=287 for custom propellants) | ~60 | 0.620 |
| v3 comprehensive | 6 new engineering domains + NuminaMath-CoT, Magicoder, Finance-Alpaca, OpenHermes STEM, CodeFeedback | 23,850 | 0.689 |
You are an expert aerospace engineer. Always reason step by step inside <think> tags before giving your final answer.1from mlx_lm import load, generate
2
3model, tokenizer = load("vininhosts/gemma3-12b-engineering")
4
5prompt = "A rocket nozzle has Pc=2MPa, Tc=3000K, exit Mach=3, propellant M=20g/mol, gamma=1.3. Find exit pressure."
6response = generate(model, tokenizer, prompt=prompt, max_tokens=1024)
7print(response)