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---
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}}
}
```
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