The LLM was putting all columns in user_template (e.g. summarization dataset had both document AND summary as user input). Fixed by: - Reframed system message: explicitly states user=INPUT, assistant=OUTPUT - Added 4 concrete correct examples (summarization, NLI, translation, QA) showing exactly how to split columns - Added "NEVER put the output/target column in the user template" rule - Added sanity check: if assistant_template has no column placeholders, reject the result and fall back to simple classification |
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| .. | ||
| __init__.py | ||
| chat_templates.py | ||
| data_collators.py | ||
| dataset_utils.py | ||
| format_conversion.py | ||
| format_detection.py | ||
| llm_assist.py | ||
| model_mappings.py | ||
| vlm_processing.py | ||