初始化项目，由ModelHub XC社区提供模型

Model: Lavanya177/SkyAssist-Llama
Source: Original Platform

README.md

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+---
+license: mit
+language:
+- en
+
+library_name: transformers
+
+pipeline_tag: text-generation
+
+base_model: meta-llama/Llama-3.2-3B-Instruct
+
+tags:
+- llama
+- qlora
+- peft
+- airline
+- customer-support
+- conversational
+- instruction-tuning
+---
+
+# ✈️ SkyAssist-Llama
+
+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.
+
+---
+
+# Model Details
+
+| 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) |
+
+---
+
+# Training Data
+
+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:
+
+- Data preprocessing
+- LLM-based convertibility classification
+- Airline domain transformation
+- post-processing and cleaning
+- JSON validation
+- Sample-based manual review
+
+The complete dataset is available on Hugging Face:
+
+**Dataset:** https://huggingface.co/datasets/Lavanya177/airline-support-tone-clean
+
+---
+
+# Training Configuration
+
+| 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 |
+
+---
+
+# Evaluation
+
+| 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.
+
+---
+
+# Intended Use
+
+SkyAssist-Llama is intended for:
+
+- Airline customer support assistants
+- Conversational AI research
+- Educational purposes
+- Domain adaptation experiments
+- LLM fine-tuning research
+
+---
+
+# Limitations
+
+This model:
+
+- does not access live airline booking systems
+- cannot retrieve reservation details
+- cannot process ticket changes or refunds
+- may generate incorrect airline-specific policies
+- should not replace official airline customer support
+
+---
+
+# Usage
+
+## Load the model
+
+```python
+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"
+)
+```
+---
+
+# Example
+
+**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.
+```
+
+---
+
+# Citation
+
+```bibtex
+@misc{skyassistllama2026,
+  title={SkyAssist-Llama: A Domain-Specific Airline Customer Support Large Language Model},
+  author={Lavanya Singh},
+  year={2026}
+}
+```
+
+# License
+
+This project is released under the MIT License.