Model Card for Model ID
Model Card — LLaMA-3 8B Linux & Programming Assistant (LoRA)
Model Details
Model Description
- Developed by: Abishek
- Model type: Large Language Model (Instruction-tuned, LoRA adapter)
- Language(s) (NLP): English
- License: Meta LLaMA 3 License (base model)
- Finetuned from model [optional]: meta-llama/Meta-Llama-3-8B-Instruct
Model Sources [optional]
Direct Use
*Linux command explanations
*Beginner-friendly programming help (Python, Git)
*Educational and learning assistance
*CLI and scripting guidance
Downstream Use
Can be integrated into chatbots or developer assistants
Suitable for educational tools or internal documentation assistants
Out-of-Scope Use
Medical, legal, or financial advice
Safety-critical or production-grade decision systems
Recommendations
Users should:
Verify generated commands before execution
Avoid using the model for sensitive or high-risk tasks
Treat outputs as guidance, not ground truth
Topics:
Linux commands (chmod, ls, permissions)
Python basics and errors
Git workflows
Data sourced from documentation-style examples and manually curated Q&A
Training Procedure
Preprocessing
Alpaca-style prompt formatting
Max sequence length: 2048 tokens
Instruction + response concatenation
Training Hyperparameters
Training regime: QLoRA (4-bit)
Optimizer: AdamW
Learning rate: 2e-4
Batch size: 1
Gradient accumulation: 8
Epochs: 1
LoRA rank (r): 16
Evaluation
Testing Data
Manual prompt-based evaluation
Linux and programming queries not seen during training
Factors
Clarity
Correctness
Domain relevance
Hallucination reduction
Metrics
Qualitative comparison against base model
Results
Improved clarity and structure for Linux explanations
Reduced generic responses
Better beginner-friendly outputs
Summary
This LoRA adapter demonstrates how QLoRA enables efficient fine-tuning of large language models on limited hardware, producing meaningful domain adaptation with minimal compute.
Environmental Impact
Hardware Type: NVIDIA T4 GPU
Hours used: ~1–1.5 hours
Cloud Provider: Google Colab (Free Tier)
Compute Region: Unknown
Carbon Emitted: Low (small-scale experiment)
Technical Specifications
Model Architecture and Objective
Decoder-only transformer (LLaMA-3)
Instruction-tuned via supervised fine-tuning (SFT)
Compute Infrastructure
Google Colab (Free Tier)
Hardware
NVIDIA T4 GPU
~16 GB VRAM
Software
PyTorch
Hugging Face Transformers
PEFT
BitsAndBytes
Unsloth
Citation
BibTeX
@misc{llama3_linux_lora,
author = {Abishek},
title = {LLaMA-3 8B Linux & Programming Assistant (LoRA)},
year = {2025},
url = {
https://huggingface.co/Master-Abi/llama3-8b-linux-assistant-lora}
}
APA
Your Name. (2025). LLaMA-3 8B Linux & Programming Assistant (LoRA). Hugging Face.
Model Card Authors
Abishek / Master-Abi
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