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Model: PraneetNS/EduMentor-Qwen3-4B-v2-FP16 Source: Original Platform
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README.md
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README.md
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---
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license: apache-2.0
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language:
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- en
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pipeline_tag: text-generation
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library_name: transformers
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base_model: PraneetNS/EduMentor-Qwen3-4B-FP16
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tags:
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- qwen3
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- education
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- engineering
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- mentor
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- llm
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- conversational
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- multimodal
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- speech
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- json
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- fine-tuned
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---
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# EduMentor Qwen3 4B v2 (FP16)
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EduMentor v2 is the second major release of EduMentor, an AI engineering mentor built for university students.
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The model is designed to provide conversational technical guidance, placement preparation, project mentoring, and structured educational responses across multiple engineering disciplines.
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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.
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---
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# Highlights
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## New in Version 2
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Compared to EduMentor v1, this release includes:
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- Fine-tuned on an expanded multi-turn engineering conversation dataset (~27K conversations).
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- Improved contextual follow-up handling.
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- Better conversational flow for tutoring sessions.
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- Stronger identity consistency as EduMentor.
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- Improved reasoning across Computer Science and core engineering subjects.
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- Enhanced placement and career guidance.
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- Better structured JSON responses for multimodal applications.
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- Verified merged FP16 checkpoint (no LoRA dependency).
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|
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---
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# Model Information
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| Property | Value |
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|----------|-------|
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| Base Model | EduMentor-Qwen3-4B-FP16 (v1) |
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| Architecture | Qwen3-4B |
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| Fine-tuning | Supervised Fine-Tuning (LoRA) |
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| Merge | Fully merged FP16 |
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| Context Length | 4096 tokens |
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| Precision | FP16 |
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| Intended Use | Engineering Mentor |
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|
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---
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# Training Dataset
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EduMentor v2 was trained on approximately 27,000 carefully curated multi-turn conversations covering engineering education.
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The dataset emphasizes:
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- realistic mentor-student interactions
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- conceptual teaching
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- problem solving
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- project guidance
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- interview preparation
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- career mentoring
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- emotional encouragement
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- structured responses
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The conversations include contextual follow-up questions to simulate natural tutoring sessions.
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---
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# Supported Domains
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## Computer Science
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- Programming Fundamentals
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- Object Oriented Programming
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- Data Structures
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- Algorithms
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- Operating Systems
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||||
- DBMS
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||||
- Computer Networks
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||||
- Software Engineering
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||||
|
||||
---
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||||
|
||||
## Artificial Intelligence
|
||||
|
||||
- Machine Learning
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||||
- Deep Learning
|
||||
- Neural Networks
|
||||
- LLMs
|
||||
- Transformers
|
||||
- RAG
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- Prompt Engineering
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- AI Deployment
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|
||||
---
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||||
|
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## Electronics
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||||
|
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- Digital Electronics
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- Analog Electronics
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- Signals
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- Communication
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- Embedded Systems
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- Microprocessors
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|
||||
---
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||||
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## Electrical Engineering
|
||||
|
||||
- Machines
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- Power Systems
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- Control Systems
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- Power Electronics
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|
||||
---
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## Mechanical Engineering
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||||
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- Thermodynamics
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- Manufacturing
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- Design
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- Strength of Materials
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- Fluid Mechanics
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|
||||
---
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## Civil Engineering
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- RCC
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- Structural Engineering
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- Surveying
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- Transportation
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- Environmental Engineering
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|
||||
---
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||||
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## Mathematics
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- Calculus
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- Linear Algebra
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- Probability
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- Statistics
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- Discrete Mathematics
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|
||||
---
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## Career Guidance
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- Placements
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- Resume Reviews
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- Internship Guidance
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- Interview Preparation
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- Learning Roadmaps
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- Project Ideas
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||||
|
||||
---
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# Response Format
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EduMentor is designed for multimodal tutoring systems.
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Typical responses follow the format:
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```json
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{
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"speech": "...",
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"display": {
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"type": "code | notes | roadmap | table | flowchart",
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"content": "..."
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},
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"follow_up": "..."
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}
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```
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This allows downstream applications to:
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- speak only the explanation
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- display diagrams separately
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- avoid reading code aloud
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- render structured educational artifacts
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|
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---
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# Intended Voice Pipeline
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|
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```
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User Speech
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│
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▼
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Speech Recognition
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│
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▼
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EduMentor v2
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│
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▼
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JSON Parser
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│
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┌────┴─────────────┐
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▼ ▼
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Speech Display
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(TTS) (Code / Notes / Roadmaps)
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```
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Recommended stack:
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- Faster-Whisper
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- EduMentor
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- llama.cpp
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- Kokoro TTS
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|
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---
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||||
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# Example
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## User
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Explain Binary Search.
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## Assistant
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```json
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{
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"speech": "Binary Search repeatedly divides the search space in half, making it much faster than linear search on sorted data.",
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"display": {
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"type": "code",
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"language": "python",
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"content": "def binary_search(...): ..."
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},
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"follow_up": "Would you like to understand the time complexity?"
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}
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```
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---
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# Usage
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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model_id = "PraneetNS/EduMentor-Qwen3-4B-v2-FP16"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype=torch.float16,
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device_map="auto"
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)
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```
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||||
---
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||||
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# Intended Applications
|
||||
|
||||
EduMentor is suitable for:
|
||||
|
||||
- AI Tutors
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- Educational Chatbots
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- Voice Assistants
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- Engineering Learning Platforms
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- Placement Preparation
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- Career Mentoring
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- Project Guidance
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||||
- Classroom Assistants
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||||
|
||||
---
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# Limitations
|
||||
|
||||
EduMentor may occasionally:
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|
||||
- generate incorrect technical information
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- require verification for safety-critical engineering tasks
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- produce imperfect JSON formatting for highly complex requests
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- benefit from external tools or retrieval for rapidly changing topics
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It should not be considered a replacement for certified professional engineering advice.
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---
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# Roadmap
|
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|
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Future versions aim to include:
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||||
|
||||
- Tool Calling
|
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- Retrieval-Augmented Generation (RAG)
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- Long-Term Student Memory
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- Personalized Learning Plans
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- Multimodal Diagram Generation
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- Real-Time Coding Assistance
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- Agentic Workflows
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|
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---
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# Citation
|
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If you use EduMentor in academic work or projects, please cite this repository.
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|
||||
---
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# Acknowledgements
|
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|
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EduMentor is built upon the Qwen3 architecture and fine-tuned to provide personalized engineering education through conversational AI.
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---
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# Creator
|
||||
|
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**Praneet N S**
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|
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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.
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29
added_tokens.json
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added_tokens.json
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{
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"</think>": 151668,
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"</tool_call>": 151658,
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"</tool_response>": 151666,
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"<think>": 151667,
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"<tool_call>": 151657,
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"<tool_response>": 151665,
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"<|PAD_TOKEN|>": 151669,
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"<|box_end|>": 151649,
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"<|box_start|>": 151648,
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"<|endoftext|>": 151643,
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"<|file_sep|>": 151664,
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"<|fim_middle|>": 151660,
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"<|fim_pad|>": 151662,
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"<|fim_prefix|>": 151659,
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"<|fim_suffix|>": 151661,
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"<|im_end|>": 151645,
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||||
"<|im_start|>": 151644,
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||||
"<|image_pad|>": 151655,
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||||
"<|object_ref_end|>": 151647,
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"<|object_ref_start|>": 151646,
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"<|quad_end|>": 151651,
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||||
"<|quad_start|>": 151650,
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"<|repo_name|>": 151663,
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||||
"<|video_pad|>": 151656,
|
||||
"<|vision_end|>": 151653,
|
||||
"<|vision_pad|>": 151654,
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"<|vision_start|>": 151652
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}
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chat_template.jinja
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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||||
{%- if messages[0].role == 'system' %}
|
||||
{{- messages[0].content + '\n\n' }}
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||||
{%- endif %}
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||||
{{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
|
||||
{%- for tool in tools %}
|
||||
{{- "\n" }}
|
||||
{{- tool | tojson }}
|
||||
{%- endfor %}
|
||||
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
|
||||
{%- else %}
|
||||
{%- if messages[0].role == 'system' %}
|
||||
{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
||||
{%- for message in messages[::-1] %}
|
||||
{%- set index = (messages|length - 1) - loop.index0 %}
|
||||
{%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
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||||
{%- set ns.multi_step_tool = false %}
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||||
{%- set ns.last_query_index = index %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- for message in messages %}
|
||||
{%- if message.content is string %}
|
||||
{%- set content = message.content %}
|
||||
{%- else %}
|
||||
{%- set content = '' %}
|
||||
{%- endif %}
|
||||
{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
||||
{%- elif message.role == "assistant" %}
|
||||
{%- set reasoning_content = '' %}
|
||||
{%- if message.reasoning_content is string %}
|
||||
{%- set reasoning_content = message.reasoning_content %}
|
||||
{%- else %}
|
||||
{%- if '</think>' in content %}
|
||||
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
||||
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- if loop.index0 > ns.last_query_index %}
|
||||
{%- if loop.last or (not loop.last and reasoning_content) %}
|
||||
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
|
||||
{%- else %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||
{%- endif %}
|
||||
{%- else %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||
{%- endif %}
|
||||
{%- if message.tool_calls %}
|
||||
{%- for tool_call in message.tool_calls %}
|
||||
{%- if (loop.first and content) or (not loop.first) %}
|
||||
{{- '\n' }}
|
||||
{%- endif %}
|
||||
{%- if tool_call.function %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{{- '<tool_call>\n{"name": "' }}
|
||||
{{- tool_call.name }}
|
||||
{{- '", "arguments": ' }}
|
||||
{%- if tool_call.arguments is string %}
|
||||
{{- tool_call.arguments }}
|
||||
{%- else %}
|
||||
{{- tool_call.arguments | tojson }}
|
||||
{%- endif %}
|
||||
{{- '}\n</tool_call>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- elif message.role == "tool" %}
|
||||
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
||||
{{- '<|im_start|>user' }}
|
||||
{%- endif %}
|
||||
{{- '\n<tool_response>\n' }}
|
||||
{{- content }}
|
||||
{{- '\n</tool_response>' }}
|
||||
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- if add_generation_prompt %}
|
||||
{{- '<|im_start|>assistant\n' }}
|
||||
{%- endif %}
|
||||
74
config.json
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74
config.json
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||||
{
|
||||
"architectures": [
|
||||
"Qwen3ForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"dtype": "float16",
|
||||
"eos_token_id": 151645,
|
||||
"head_dim": 128,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 2560,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 9728,
|
||||
"layer_types": [
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
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|
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|
||||
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|
||||
16
special_tokens_map.json
Normal file
16
special_tokens_map.json
Normal file
@@ -0,0 +1,16 @@
|
||||
{
|
||||
"eos_token": {
|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:d7430e9138b76e93fb6f93462394d236b411111aef53cb421ba97d2691040cca
|
||||
size 11423114
|
||||
235
tokenizer_config.json
Normal file
235
tokenizer_config.json
Normal file
@@ -0,0 +1,235 @@
|
||||
{
|
||||
"add_prefix_space": false,
|
||||
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||||
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|
||||
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||||
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||||
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||||
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|
||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user