README.md

---
tags:
- computer-engineering
- llama-3
- 3b
- lora
- 4bit
license: llama3.2
license_link: https://llama.meta.com/llama3/license
base_model:
- meta-llama/Llama-3.2-3B-Instruct
datasets:
-  Wikitext-2-raw-v1
-  STEM-AI-mtl 
-  custom-computer-engineering-corpus
-  technical-documentation
-  hardware-specs
---

# 🖥️ Llama-3.2-3B-Computer-Engineering-LLM

**Specialized AI Assistant for Computer Engineering**  
*Fine-tuned Meta-Llama-3-3B with 4-bit quantization + LoRA adapters*

<div align="center">
  <a href="https://github.com/IrfanUruchi/Llama-3.2-3B-Computer-Engineering-LLM">
    <img src="https://img.shields.io/badge/🔗_GitHub-Repo-181717?style=for-the-badge&logo=github" alt="GitHub">
  </a>
  <a href="https://huggingface.co/Irfanuruchi/Llama-3.2-3B-Computer-Engineering-LLM">
    <img src="https://img.shields.io/badge/🤗_HuggingFace-Model_Repo-FFD21F?style=for-the-badge" alt="HuggingFace">
  </a>
  <br>
  <img src="https://img.shields.io/badge/Model_Size-3.2B_parameters-blue" alt="Model Size">
  <img src="https://img.shields.io/badge/Quantization-4bit-green" alt="Quantization">
  <img src="https://img.shields.io/badge/Adapter-LoRA-orange" alt="Adapter">
  <img src="https://img.shields.io/badge/Context-8k-lightgrey" alt="Context">
  <img src="https://img.shields.io/badge/License-Llama_3.2-yellow" alt="License">
</div>


## 📜 License Compliance Notice
This model is derived from Meta's Llama 3.2 and is governed by the [Llama 3.2 Community License](https://llama.meta.com/llama3/license). By using this model, you agree to:

- Not use the model or its outputs to improve other LLMs
- Not use the model for commercial purposes without separate agreement
- Include attribution to Meta and this project
- Accept the license's acceptable use policy

---

## 🛠️ Technical Specifications

### Architecture
| Component              | Implementation Details          |
|------------------------|---------------------------------|
| Base Model             | Meta-Llama-3-3B-Instruct       |
| Quantization           | 4-bit via BitsAndBytes         |
| Adapter                | LoRA (r=16, alpha=32)          |
| Training Framework     | PyTorch + HuggingFace Ecosystem|
| Context Window         | 8,192 tokens                   |

### Training Data
- Curated computer engineering corpus 
- Key domains covered:
  - Computer architecture
  - Embedded systems
  - VLSI design
  - Hardware description languages
  - Low-level programming

---

```python

from transformers import AutoTokenizer, AutoModelForCausalLM

model_id = "Irfanuruchi/Llama-3.2-3B-Computer-Engineering-LLM"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    device_map="auto",
    torch_dtype="auto"
)

prompt = """You are a computer engineering expert. Explain concisely:
Q: What's the difference between RISC and CISC architectures?
A:"""

inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
outputs = model.generate(
    **inputs,
    max_new_tokens=150,
    temperature=0.7,
    do_sample=True
)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))

```

## Responsible use 

This model inherits all use restrictions from the Llama 3.2 license. Special considerations:

Not for production deployment without compliance review
Outputs should be verified by domain experts
Knowledge cutoff: July 2024

## Citation

If using this model in research, please cite:

```bibtex
@misc{llama3.2-computer-eng,
  author = {Irfanuruchi},
  title = {Llama-3.2-3B-Computer-Engineering-LLM},
  year = {2025},
  publisher = {HuggingFace},
  howpublished = {\url{https://huggingface.co/Irfanuruchi/Llama-3.2-3B-Computer-Engineering-LLM}}
}
```