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| [text-to-python.ipynb](./text-to-code/text-to-python.ipynb) | Text-to-Code | Generate Python code from natural language instructions with validation and evaluation |
| [text-to-python-evol.ipynb](./text-to-code/text-to-python-evol.ipynb) | Text-to-Code | Build advanced Python code generation with evolutionary improvements and iterative refinement |
| [text-to-sql.ipynb](./text-to-code/text-to-sql.ipynb) | Text-to-Code | Create SQL queries from natural language descriptions with validation and testing |
| [japanese_commonsense_qa_data_generator_nemotron_persona_jp_seed.ipynb](./nemotron-persona-jp/japanese_commonsense_qa_data_generator_nemotron_persona_jp_seed.ipynb) | Text-to-Code | Create SQL queries from natural language descriptions with validation and testing |
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"id": "header",
"metadata": {},
"source": [
"# 🎨 NeMo Data Designer: Japanese Commonsense Reasoning Dataset Generation (Improved Version)\n",
"# 🎨 NeMo Data Designer: Japanese Commonsense Reasoning Dataset Generation\n",
"\n",
"#### 📚 Overview\n",
"\n",
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"### What We Did\n",
"1. ✅ Correctly configured nvidia/Nemotron-Personas-Japan as seed data\n",
"2. ✅ Generated data by directly referencing seed data columns\n",
"3. ✅ Generated synthetic data for jcommonsenseqa and commonsensemoralja\n",
"3. ✅ Generated synthetic data for jcommonsenseqa\n",
"4. ✅ Created 2 versions: with and without seed data\n",
"5. ✅ Quality evaluation using LLM-as-a-Judge\n",
"6. ✅ Generated quality comparison report\n"
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