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Lavanya177/SkyAssist-Llama
SkyAssist-Llama is a text generation model from Lavanya177. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
SkyAssist-Llama is a domain-specific airline customer support large language model created by fine-tuning Meta Llama 3.2 3B Instruct using QLoRA (Quantized Low-Rank Adaptation).
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From the Hugging Face model README
SkyAssist-Llama is a domain-specific airline customer support large language model created by fine-tuning Meta Llama 3.2 3B Instruct using QLoRA (Quantized Low-Rank Adaptation).
The model is designed to generate professional, empathetic, and context-aware responses for common airline customer support scenarios, including flight delays, cancellations, baggage inquiries, booking modifications, refunds, and check-in assistance.
| Property | Value |
|---|---|
| Base Model | Meta Llama 3.2 3B Instruct |
| Fine-tuning Method | QLoRA |
| Task | Airline Customer Support |
| Language | English |
| Architecture | Decoder-only Transformer |
| Training Objective | Supervised Fine-Tuning (SFT) |
The model was trained on 2,666 airline customer support conversations.
Rather than relying on an existing airline dataset, the training data was created through a multi-stage automated pipeline that transformed general customer support conversations into realistic airline-specific interactions.
The dataset generation process included:
The complete dataset is available on Hugging Face:
Dataset: https://huggingface.co/datasets/Lavanya177/airline-support-tone-clean
| Parameter | Value |
|---|---|
| Base Model | Llama 3.2 3B Instruct |
| Fine-Tuning Method | QLoRA |
| LoRA Rank | 32 |
| LoRA Alpha | 64 |
| Learning Rate | 1e-3 |
| Epochs | 3 |
| Batch Size | 8 |
| Gradient Accumulation | 4 |
| Optimizer | AdamW |
| Scheduler | Cosine |
| Max Sequence Length | 2048 |
| Precision | BF16 |
| Metric | Value |
|---|---|
| Training Loss | 0.4615 |
| Validation Loss | 0.5557 |
| Test Loss | 0.62 |
The model demonstrates good convergence while maintaining strong generalization on unseen airline customer support conversations.
SkyAssist-Llama is intended for:
This model:
from transformers import AutoTokenizer, AutoModelForCausalLM
model_name = "Lavanya177/SkyAssist-Llama"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
model_name,
device_map="auto"
)
System Prompt
You are a professional airline customer support assistant...
User
My baggage has not arrived. What should I do?
Assistant
I'm sorry to hear that your baggage has not arrived. I understand how frustrating this situation can be.
Please provide your baggage claim number, flight number, travel date, and destination airport so I can assist you further. If you have already reported the issue at the airport, please also share your Property Irregularity Report (PIR) reference number.
Once these details are available, the airline can begin tracking your baggage and provide updates on its status.
@misc{skyassistllama2026,
title={SkyAssist-Llama: A Domain-Specific Airline Customer Support Large Language Model},
author={Lavanya Singh},
year={2026}
}
This project is released under the MIT License.