CoolFace
Modelpublic

psdba/deepseek-mcq-trainer-mohammedsayeeduddin-lora

sourceHugging Faceotherupdated 9mo agoView on Hugging Face
1likes15downloads
Model Card

DeepSeek MCQ Trainer (LoRA) — by Mohammed Sayeeduddin

Model Details

  • —Model name: psdba/deepseek-mcq-trainer-mohammedsayeeduddin-lora
  • —Developed by: Mohammed Sayeeduddin
  • —Model type: LoRA adapter (PEFT) fine-tuned for structured MCQ generation
  • —Base model: deepseek-ai/deepseek-coder-1.3b-instruct
  • —Primary use: Instructor-grade MCQ generation in strict JSON format for IT training
  • —Language(s): English
  • —License: This repository contains LoRA adapter weights only. Usage is subject to the license of the base model (deepseek-ai/deepseek-coder-1.3b-instruct). Please review and comply with that license before commercial or redistribution use.

Model Description

This is a specialist training model designed to generate multiple-choice questions (MCQs) in a strict, machine-readable JSON schema.

The adapter was fine-tuned to produce:

  • —4 options (A/B/C/D)
  • —exactly 1 correct answer
  • —short explanation
  • —JSON-only responses (no markdown, no extra commentary)

Intended Use

Direct Use

  • —Corporate training MCQs (FastAPI, Docker/Linux, Python Core, LLM/RAG)
  • —Classroom quizzes and practice tests
  • —Building MCQ datasets for LMS/Excel ingestion

Downstream Use

  • —Integration into training platforms (MCQ generators, exam portals)
  • —Dataset generation pipelines (JSON → CSV → LMS)

Out-of-Scope Use

  • —Medical / legal / financial advice
  • —Open-domain chat or creative writing
  • —High-stakes decisions without human validation

Bias, Risks, and Limitations

  • —MCQs may still contain imperfections or ambiguous distractors.
  • —Always validate questions before real exams or certifications.
  • —Model can hallucinate if prompts are unclear or request unsupported topics.

How to Get Started

Install

bash
pip install -U transformers peft accelerate