README.md

---
license: apache-2.0
language:
- en
pipeline_tag: text-generation
tags:
- chatbot
- conversational-ai
- instruction-tuning
- large-language-model
- education
---
# Qwen-Chatbot: Instruction-Tuned Educational Conversational Model

## Overview
Qwen-Chatbot is a fine-tuned large language model designed for educational conversational use cases. The model was trained to provide structured, clear, and context-aware responses, with emphasis on explanation quality and instructional dialogue rather than open-ended creativity.

## Task
- Educational chatbot interaction
- Question answering with explanations
- Conversational tutoring assistance

## Training Details
- Base model: Qwen family language model
- Fine-tuning approach: Instruction tuning
- Dataset: Custom-curated conversational instruction data
- Training environment: Single-GPU setup
- Objective: Improve response clarity, coherence, and instructional usefulness

## Intended Use
This model is intended for academic research, educational chatbots, and experimentation with conversational AI systems. It is not designed for deployment in production or safety-critical environments.

## Limitations
- The model has not been evaluated using standard conversational benchmarks.
- Responses may be verbose for simple queries.
- Hallucinations may occur for out-of-domain or ambiguous prompts.

## Notes
- This model was developed as part of MSc-level academic coursework.
- The focus was on conversational structure and pedagogical clarity.
- Future work may include dataset expansion and formal quantitative evaluation.

## Changelog
- August 2025: Initial fine-tuned release
- Planned: Improved instruction dataset and evaluation metrics

## Example Usage
```python
from transformers import pipeline

chatbot = pipeline("text-generation", model="ushasree2001/qwen_chatbot")
chatbot("How to find the factors of a number?")