cs-552-2026-ma-que/general_knowledge_model
The cs-552-2026-ma-que/general_knowledge_model is a 1.7 billion parameter language model developed by Ma Que, fine-tuned from Qwen/Qwen3-1.7B-Base. It is specifically designed for general knowledge multiple-choice answering, providing reasoning-style responses with a final boxed answer. This model excels at academic benchmark tasks requiring structured, reasoned answers to general knowledge questions.
Loading preview...
Overview
The cs-552-2026-ma-que/general_knowledge_model is a specialized language model developed by Ma Que for the EPFL CS-552 course. It is based on the Qwen3-1.7B-Base model and has undergone LoRA SFT (Supervised Fine-Tuning) to excel in general knowledge multiple-choice answering. The model is designed to produce reasoning traces before committing to a final, single-letter boxed answer, adhering to a specific output contract for automated parsing.
Key Capabilities
- General Knowledge Multiple-Choice Answering: Optimized to read questions with lettered options and select the correct one.
- Reasoning-Style Responses: Trained to generate internal thought processes (
<think>...</think>) before providing the final answer. - Structured Output: Emits the final answer in the format
\boxed{X}for compatibility with parsers like OpenCompass/vLLM. - LoRA Fine-Tuning: Utilizes LoRA with rank 256 and alpha 256, targeting key attention and feed-forward projection layers for efficient adaptation.
Intended Use & Limitations
This model is primarily a research artifact for the CS-552 general knowledge benchmark. It is intended for academic evaluation and producing structured multiple-choice answers. Users should be aware that it is not an authoritative factual system and may contain outdated, incomplete, or incorrect information. Outputs require verification before any real-world or safety-critical applications.