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Irfanuruchi/
Llama-3.2-3B-Computer-Engineering-LLM

Name: Llama-3.2-3B-Computer-Engineering-LLM
Availability: InStock

custom-computer-engineering-corpus

technical-documentation

hardware-specs

meta-llama/Llama-3.2-3B-Instruct

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🖥️ 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

GitHub

📜 License Compliance Notice

This model is derived from Meta's Llama 3.2 and is governed by the Llama 3.2 Community 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}}
}