| --- |
| license: apache-2.0 |
| base_model: |
| - microsoft/phi-2 |
| --- |
| # NCU Smart LLM (phi2-ncu) — Smart LLM Fine-tuned for NCU Tasks |
|
|
| <p align="center"> |
| <img src="https://huggingface.co/pranav2711/phi2-ncu-model/resolve/main/NCU-Logo.png" alt="NCU Logo" width="350"/> |
| </p> |
|
|
| > A lightweight, instruction-tuned version of [Microsoft's Phi-2](https://huggingface.co/microsoft/phi-2), customized for use cases and conversations related to The NorthCap University (NCU), India. |
| > Fine-tuned using LoRA on 1,098 high-quality examples, it's optimized for academic, administrative, and smart campus queries. |
|
|
| --- |
|
|
| ## Highlights |
|
|
| * **Base Model:** `microsoft/phi-2` (2.7B parameters) |
| * **Fine-tuned Using:** Low-Rank Adaptation (LoRA) + PEFT + Hugging Face Transformers |
| * **Dataset:** University questions, FAQs, policies, academic support queries, smart campus data |
| * **Training Environment:** Google Colab (T4 GPU), 4 epochs, batch size 1, no FP16 |
| * **Final Format:** Full model weights (`.safetensors`) + tokenizer |
|
|
| --- |
|
|
| ## Model Access |
|
|
| | Platform | Access Method | |
| | ------------------ | --------------------------------------------------------------------------- | |
| | Hugging Face | [phi2-ncu-model](https://huggingface.co/pranav2711/phi2-ncu-model) | |
| | Hugging Face Space | [Live Chatbot Demo](https://huggingface.co/spaces/pranav2711/phi2-ncu-chat-space) | |
| | Ollama (Offline) | `ollama create phi2-ncu -f Modelfile` *(self-hosted only)* | |
|
|
| --- |
|
|
| ## Try It Online |
|
|
| ### Gradio Web Chat (Hugging Face Space) (Runs Slow because of free CPU Hardware) |
|
|
| ```bash |
| 👉 Visit: https://huggingface.co/spaces/pranav2711/phi2-ncu-chat-space |
| ``` |
|
|
| * Built using `Gradio`, deployed on Hugging Face Spaces |
|
|
| --- |
|
|
| ## How to Use Locally (Hugging Face Transformers) |
|
|
| ```bash |
| pip install transformers accelerate peft |
| ``` |
|
|
| ```python |
| from transformers import AutoTokenizer, AutoModelForCausalLM |
| from peft import PeftModel, PeftConfig |
| |
| # Load adapter config |
| adapter_path = "pranav2711/phi2-ncu-model" |
| base_model = "microsoft/phi-2" |
| |
| # Load tokenizer and base |
| tokenizer = AutoTokenizer.from_pretrained(base_model) |
| model = AutoModelForCausalLM.from_pretrained(base_model, device_map="auto") |
| |
| # Load fine-tuned adapter |
| model = PeftModel.from_pretrained(model, adapter_path) |
| |
| # Inference |
| input_prompt = "### Question:\nHow can I apply for re-evaluation at NCU?\n\n### Answer:" |
| inputs = tokenizer(input_prompt, return_tensors="pt").to("cuda") |
| outputs = model.generate(**inputs, max_new_tokens=200) |
| print(tokenizer.decode(outputs[0], skip_special_tokens=True)) |
| ``` |
|
|
| --- |
|
|
| ## How to Use with Ollama (Offline) |
|
|
| > This works only **locally** via `ollama create` and **not yet shareable** as public Ollama model hub is restricted. |
|
|
| ### Folder Structure |
|
|
| ``` |
| phi2-ncu/ |
| ├── Modelfile |
| └── model/ |
| ├── model.safetensors |
| ├── config.json |
| ├── tokenizer.json |
| ├── tokenizer_config.json |
| ├── vocab.json |
| ├── merges.txt |
| ``` |
|
|
| ### Steps |
|
|
| ```bash |
| ollama create phi2-ncu -f Modelfile |
| ollama run phi2-ncu |
| ``` |
|
|
| --- |
|
|
| ## Example Dataset Format (Used for Training) |
|
|
| ```json |
| { |
| "instruction": "How do I get my degree certificate?", |
| "input": "I'm a 2023 BTech passout from CSE at NCU.", |
| "output": "You can collect your degree certificate from the admin block on working days between 9AM and 4PM. Carry a valid ID proof." |
| } |
| ``` |
|
|
| Formatted as: |
|
|
| ``` |
| ### Question: |
| How do I get my degree certificate? |
| I'm a 2023 BTech passout from CSE at NCU. |
| |
| ### Answer: |
| You can collect your degree certificate... |
| ``` |
|
|
| --- |
|
|
| ## Training Strategy |
|
|
| * Used `LoRA` with rank=8, alpha=16 |
| * Tokenized to max length = 512 |
| * Used `Trainer` with `fp16=False` to avoid CUDA AMP issues |
| * Batch size = 1, Epochs = 4 |
| * Trained on Google Colab (T4), saving final full weights |
|
|
| --- |
|
|
| ## License |
|
|
| [Apache 2.0](https://huggingface.co/pranav2711/phi2-ncu-model/resolve/main/LICENSE) |
|
|
| ## About NCU |
|
|
| **The NorthCap University**, Gurugram (formerly ITM University), is a multidisciplinary university with programs in engineering, management, law, and sciences. |
|
|
| This model was created as part of a research initiative to explore AI for academic services, campus automation, and local LLM deployments. |
|
|
| ## Contribute |
|
|
| Have better FAQs or data? Want to train on your college corpus? Fork the repo or raise a PR at: |
|
|
| 👉 [https://github.com/pranav2711/ncu-smartllm](https://github.com/pranav2711/ncu-smartllm) |
|
|
