NCU SmartLLM โ Mistral 7B Fine-tuned on NorthCap University Curriculum
NCU SmartLLM is a domain-specialized version of Mistral-7B-Instruct, fine-tuned on real academic material from The NorthCap University (NCU). It is built to assist with college-level instruction, syllabus summarization, technical definitions, and Q&A across engineering and computer science disciplines.
Features
- Fine-tuned on 1200+ course entries from NCU's official syllabus
- Based on
Mistral-7B-Instruct
, known for concise and instruction-following responses - Trained using LoRA (PEFT) and quantized to 4-bit (bnb + bitsandbytes)
- Combined data: structured course PDFs + scraped university site content
- Optimized for academic question answering and domain-specific tasks
Usage
from transformers import pipeline
pipe = pipeline(
"text-generation",
model="pranav2711/ncu-smartllm",
tokenizer="pranav2711/ncu-smartllm",
device_map="auto"
)
prompt = """### Instruction:
What is the role of the compiler and linker in the C language?
### Response:
"""
output = pipe(prompt, max_new_tokens=200, temperature=0.7)
print(output[0]["generated_text"])
Training Details
Base model:
mistralai/Mistral-7B-Instruct-v0.1
Method: Parameter-efficient fine-tuning with LoRA using
PEFT
Quantization: 4-bit (
bnb4bit
) for fast training on Colab ProFrameworks:
transformers
,bitsandbytes
,peft
,accelerate
Data sources:
Official Syllabus PDFs
(official NCU syllabus)- Text scraped from https://www.ncuindia.edu
Training Time: ~3.5 hours on A100 via Google Colab Pro
Example Prompts
### Instruction:
Explain the difference between a compiler and an interpreter.
### Response:
A compiler translates an entire program into machine code before execution...
### Instruction:
What is the credit structure and content for FOCP-I?
### Response:
FOCP-I (CSL106) is structured as (2-0-4) credits...
### Instruction:
List types of number systems in computing and their conversions.
### Response:
There are four primary number systems: Binary, Decimal, Octal, and Hexadecimal...
License
This model is licensed under the Apache 2.0 License.
Author
Built and fine-tuned by @pranav2711 Project: SmartLLM for NCU โ empowering education with custom LLMs.
Citation
If you use this model in academic work or research:
@misc{ncu2024smartllm,
title = {NCU SmartLLM: Fine-tuned Mistral 7B on Academic Syllabus},
author = {Pranav},
year = {2024},
publisher = {Hugging Face},
howpublished = {\url{https://huggingface.co/pranav2711/ncu-smartllm}}
}
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