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Irfanuruchi/Llama-3.2-1B-Computer-Engineering-LLM

sourceHugging Facellama3.2updated 10mo agoView on Hugging Face
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Specialized 1B Parameter Model for Computer Engineering Fine-tuned with LoRA on 8-bit quantized Llama-3-1B

<div align="center"> <a href="https://github.com/IrfanUruchi/Llama-3.2-1B-ComputerEngineeringLLM"> <img src="https://img.shields.io/badge/๐Ÿ”—GitHub-Repo-181717?style=for-the-badge&logo=github" alt="GitHub"> </a> <a href="https://huggingface.co/Irfanuruchi/Llama-3.2-1B-Computer-Engineering-LLM"> <img src="https://img.shields.io/badge/๐Ÿค—HuggingFace-ModelRepo-FFD21F?style=for-the-badge" alt="HuggingFace"> </a> <br> <img src="https://img.shields.io/badge/ModelSize-1B_parameters-blue" alt="Model Size"> <img src="https://img.shields.io/badge/Quantization-8bit-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"> </div>


๐Ÿ› ๏ธ Technical Specifications

Architecture

ComponentSpecification
Base ModelMeta-Llama-3-1B
Hidden Size2048
Layers16
Attention Heads32
Quantization8-bit via BitsAndBytes
Fine-Tuning MethodLoRA (Low-Rank Adaptation)
Tokenizer Vocabulary128,256 tokens

Training Data

  • โ€”Wikitext-2-raw-v1 (General knowledge)
  • โ€”Custom computer engineering corpus:
  • โ€”Hardware design principles
  • โ€”Processor architectures
  • โ€”Embedded systems documentation

Installation and usage

Option 1: From Hugging Face Hub (Recommended)

python

model_id = "Irfanuruchi/Llama-3.2-1B-Computer-Engineering-LLM"

Option 2: Local Installation (Git LFS Required)

python

from transformers import AutoModelForCausalLM, AutoTokenizer

# Replace with your local path
model_path = "./Llama-3.2-1B-ComputerEngineeringLLM"  

Recomended Config

python
outputs = model.generate(
    **inputs,
    max_new_tokens=200,
    temperature=0.7, 
    top_p=0.9,     
    do_sample=True,
    repetition_penalty=1.1  
)

Licence complience

This model is governed by the Llama 3.2 Community License. Key requirements:

Non-commercial use only Attribution to Meta required Cannot be used to train other LLMs Attribution Notice: "Llama 3.2 is licensed under the Llama 3.2 Community License, Copyright ยฉ Meta Platforms, Inc."


Limitations

Specialized for computer engineering (general performance may vary) Occasional repetition in outputs Requires prompt engineering for optimal results Knowledge cutoff: January 2025


Citation

If using for academic research, please cite:

bibtex
@misc{llama3.2-1b-eng-2025,
  title = {Llama-3.2-1B-Computer-Engineering-LLM},
  author = {Irfanuruchi},
  year = {2025},
  publisher = {Hugging Face},
  url = {https://huggingface.co/Irfanuruchi/Llama-3.2-1B-Computer-Engineering-LLM},
}