初始化项目，由ModelHub XC社区提供模型
Model: PraneetNS/EduMentor-Qwen3-4B-v2-FP16 Source: Original Platform
This commit is contained in:
ModelHub XC
326
README.md
Normal file
326
README.md
Normal file
@@ -0,0 +1,326 @@
|
||||
---
|
||||
license: apache-2.0
|
||||
language:
|
||||
- en
|
||||
pipeline_tag: text-generation
|
||||
library_name: transformers
|
||||
base_model: PraneetNS/EduMentor-Qwen3-4B-FP16
|
||||
tags:
|
||||
- qwen3
|
||||
- education
|
||||
- engineering
|
||||
- mentor
|
||||
- llm
|
||||
- conversational
|
||||
- multimodal
|
||||
- speech
|
||||
- json
|
||||
- fine-tuned
|
||||
---
|
||||
|
||||
# EduMentor Qwen3 4B v2 (FP16)
|
||||
|
||||
EduMentor v2 is the second major release of EduMentor, an AI engineering mentor built for university students.
|
||||
|
||||
The model is designed to provide conversational technical guidance, placement preparation, project mentoring, and structured educational responses across multiple engineering disciplines.
|
||||
|
||||
Unlike a generic chatbot, EduMentor is optimized for voice-first tutoring systems where spoken explanations are separated from visual artifacts such as code, diagrams, roadmaps, tables, and notes.
|
||||
|
||||
---
|
||||
|
||||
# Highlights
|
||||
|
||||
## New in Version 2
|
||||
|
||||
Compared to EduMentor v1, this release includes:
|
||||
|
||||
- Fine-tuned on an expanded multi-turn engineering conversation dataset (~27K conversations).
|
||||
- Improved contextual follow-up handling.
|
||||
- Better conversational flow for tutoring sessions.
|
||||
- Stronger identity consistency as EduMentor.
|
||||
- Improved reasoning across Computer Science and core engineering subjects.
|
||||
- Enhanced placement and career guidance.
|
||||
- Better structured JSON responses for multimodal applications.
|
||||
- Verified merged FP16 checkpoint (no LoRA dependency).
|
||||
|
||||
---
|
||||
|
||||
# Model Information
|
||||
|
||||
| Property | Value |
|
||||
|----------|-------|
|
||||
| Base Model | EduMentor-Qwen3-4B-FP16 (v1) |
|
||||
| Architecture | Qwen3-4B |
|
||||
| Fine-tuning | Supervised Fine-Tuning (LoRA) |
|
||||
| Merge | Fully merged FP16 |
|
||||
| Context Length | 4096 tokens |
|
||||
| Precision | FP16 |
|
||||
| Intended Use | Engineering Mentor |
|
||||
|
||||
---
|
||||
|
||||
# Training Dataset
|
||||
|
||||
EduMentor v2 was trained on approximately 27,000 carefully curated multi-turn conversations covering engineering education.
|
||||
|
||||
The dataset emphasizes:
|
||||
|
||||
- realistic mentor-student interactions
|
||||
- conceptual teaching
|
||||
- problem solving
|
||||
- project guidance
|
||||
- interview preparation
|
||||
- career mentoring
|
||||
- emotional encouragement
|
||||
- structured responses
|
||||
|
||||
The conversations include contextual follow-up questions to simulate natural tutoring sessions.
|
||||
|
||||
---
|
||||
|
||||
# Supported Domains
|
||||
|
||||
## Computer Science
|
||||
|
||||
- Programming Fundamentals
|
||||
- Object Oriented Programming
|
||||
- Data Structures
|
||||
- Algorithms
|
||||
- Operating Systems
|
||||
- DBMS
|
||||
- Computer Networks
|
||||
- Software Engineering
|
||||
|
||||
---
|
||||
|
||||
## Artificial Intelligence
|
||||
|
||||
- Machine Learning
|
||||
- Deep Learning
|
||||
- Neural Networks
|
||||
- LLMs
|
||||
- Transformers
|
||||
- RAG
|
||||
- Prompt Engineering
|
||||
- AI Deployment
|
||||
|
||||
---
|
||||
|
||||
## Electronics
|
||||
|
||||
- Digital Electronics
|
||||
- Analog Electronics
|
||||
- Signals
|
||||
- Communication
|
||||
- Embedded Systems
|
||||
- Microprocessors
|
||||
|
||||
---
|
||||
|
||||
## Electrical Engineering
|
||||
|
||||
- Machines
|
||||
- Power Systems
|
||||
- Control Systems
|
||||
- Power Electronics
|
||||
|
||||
---
|
||||
|
||||
## Mechanical Engineering
|
||||
|
||||
- Thermodynamics
|
||||
- Manufacturing
|
||||
- Design
|
||||
- Strength of Materials
|
||||
- Fluid Mechanics
|
||||
|
||||
---
|
||||
|
||||
## Civil Engineering
|
||||
|
||||
- RCC
|
||||
- Structural Engineering
|
||||
- Surveying
|
||||
- Transportation
|
||||
- Environmental Engineering
|
||||
|
||||
---
|
||||
|
||||
## Mathematics
|
||||
|
||||
- Calculus
|
||||
- Linear Algebra
|
||||
- Probability
|
||||
- Statistics
|
||||
- Discrete Mathematics
|
||||
|
||||
---
|
||||
|
||||
## Career Guidance
|
||||
|
||||
- Placements
|
||||
- Resume Reviews
|
||||
- Internship Guidance
|
||||
- Interview Preparation
|
||||
- Learning Roadmaps
|
||||
- Project Ideas
|
||||
|
||||
---
|
||||
|
||||
# Response Format
|
||||
|
||||
EduMentor is designed for multimodal tutoring systems.
|
||||
|
||||
Typical responses follow the format:
|
||||
|
||||
```json
|
||||
{
|
||||
"speech": "...",
|
||||
"display": {
|
||||
"type": "code | notes | roadmap | table | flowchart",
|
||||
"content": "..."
|
||||
},
|
||||
"follow_up": "..."
|
||||
}
|
||||
```
|
||||
|
||||
This allows downstream applications to:
|
||||
|
||||
- speak only the explanation
|
||||
- display diagrams separately
|
||||
- avoid reading code aloud
|
||||
- render structured educational artifacts
|
||||
|
||||
---
|
||||
|
||||
# Intended Voice Pipeline
|
||||
|
||||
```
|
||||
User Speech
|
||||
│
|
||||
▼
|
||||
Speech Recognition
|
||||
│
|
||||
▼
|
||||
EduMentor v2
|
||||
│
|
||||
▼
|
||||
JSON Parser
|
||||
│
|
||||
┌────┴─────────────┐
|
||||
▼ ▼
|
||||
Speech Display
|
||||
(TTS) (Code / Notes / Roadmaps)
|
||||
```
|
||||
|
||||
Recommended stack:
|
||||
|
||||
- Faster-Whisper
|
||||
- EduMentor
|
||||
- llama.cpp
|
||||
- Kokoro TTS
|
||||
|
||||
---
|
||||
|
||||
# Example
|
||||
|
||||
## User
|
||||
|
||||
Explain Binary Search.
|
||||
|
||||
## Assistant
|
||||
|
||||
```json
|
||||
{
|
||||
"speech": "Binary Search repeatedly divides the search space in half, making it much faster than linear search on sorted data.",
|
||||
|
||||
"display": {
|
||||
"type": "code",
|
||||
"language": "python",
|
||||
"content": "def binary_search(...): ..."
|
||||
},
|
||||
|
||||
"follow_up": "Would you like to understand the time complexity?"
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
# Usage
|
||||
|
||||
```python
|
||||
from transformers import AutoTokenizer, AutoModelForCausalLM
|
||||
import torch
|
||||
|
||||
model_id = "PraneetNS/EduMentor-Qwen3-4B-v2-FP16"
|
||||
|
||||
tokenizer = AutoTokenizer.from_pretrained(model_id)
|
||||
|
||||
model = AutoModelForCausalLM.from_pretrained(
|
||||
model_id,
|
||||
torch_dtype=torch.float16,
|
||||
device_map="auto"
|
||||
)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
# Intended Applications
|
||||
|
||||
EduMentor is suitable for:
|
||||
|
||||
- AI Tutors
|
||||
- Educational Chatbots
|
||||
- Voice Assistants
|
||||
- Engineering Learning Platforms
|
||||
- Placement Preparation
|
||||
- Career Mentoring
|
||||
- Project Guidance
|
||||
- Classroom Assistants
|
||||
|
||||
---
|
||||
|
||||
# Limitations
|
||||
|
||||
EduMentor may occasionally:
|
||||
|
||||
- generate incorrect technical information
|
||||
- require verification for safety-critical engineering tasks
|
||||
- produce imperfect JSON formatting for highly complex requests
|
||||
- benefit from external tools or retrieval for rapidly changing topics
|
||||
|
||||
It should not be considered a replacement for certified professional engineering advice.
|
||||
|
||||
---
|
||||
|
||||
# Roadmap
|
||||
|
||||
Future versions aim to include:
|
||||
|
||||
- Tool Calling
|
||||
- Retrieval-Augmented Generation (RAG)
|
||||
- Long-Term Student Memory
|
||||
- Personalized Learning Plans
|
||||
- Multimodal Diagram Generation
|
||||
- Real-Time Coding Assistance
|
||||
- Agentic Workflows
|
||||
|
||||
---
|
||||
|
||||
# Citation
|
||||
|
||||
If you use EduMentor in academic work or projects, please cite this repository.
|
||||
|
||||
---
|
||||
|
||||
# Acknowledgements
|
||||
|
||||
EduMentor is built upon the Qwen3 architecture and fine-tuned to provide personalized engineering education through conversational AI.
|
||||
|
||||
---
|
||||
|
||||
# Creator
|
||||
|
||||
**Praneet N S**
|
||||
|
||||
EduMentor is an ongoing effort to build an AI mentor capable of assisting engineering students through natural conversations, structured explanations, and voice-first educational experiences.
|
||||
Reference in New Issue
Block a user