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---
language:
- en
- ko
tags:
- qwen
- lora
- rag
- instruction-tuning
- email
- qwen-2.5
- peft
- question-answering
library_name: peft
pipeline_tag: text-generation
license: mit
---
# Qwen-RAG-LoRA
This repository contains LoRA weights for [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct), fine-tuned for email-based question answering tasks. The model has been trained to handle both English and Korean queries about email content.
## Model Description
- **Base Model:** Qwen/Qwen2.5-7B-Instruct
- **Training Type:** LoRA (Low-Rank Adaptation)
- **Checkpoint:** checkpoint-600
- **Languages:** English and Korean
- **Task:** Email-based Question Answering
- **Domain:** Email Content
## Training Details
### LoRA Configuration
```python
lora_config = LoraConfig(
r=8,
lora_alpha=32,
target_modules=["q_proj", "k_proj", "v_proj", "o_proj", "gate_proj", "up_proj", "down_proj"],
lora_dropout=0.1,
bias="none",
task_type="CAUSAL_LM"
)
```
## Usage with vLLM
```python
from vllm import LLM, SamplingParams
from vllm.lora.request import LoRARequest
# Initialize LLM with LoRA support
llm = LLM(
model="Qwen/Qwen2.5-7B-Instruct",
tensor_parallel_size=2,
enable_lora=True
)
sampling_params = SamplingParams(temperature=0.0, max_tokens=50)
# Create LoRA request
lora_request = LoRARequest(
"rag_adapter",
1,
"doubleyyh/qwen-rag-lora" # HuggingFace repo name
)
# Example prompt
prompt = """Using the context provided below, answer the question concisely. Respond in Korean if the question is in Korean, and in English if the question is in English.
Context: subject: Meeting Schedule Update
from: [['John Smith', '[email protected]']]
to: [['Team', '[email protected]']]
text_body: The project review meeting is rescheduled to 3 PM tomorrow.
Question: When is the meeting rescheduled to?
Answer: """
# Generate with LoRA
outputs = llm.generate([prompt], sampling_params, lora_request=lora_request)
print(outputs[0].outputs[0].text)
```
## Example Input/Output
```
# English Query
Q: When is the project review scheduled?
A: The project review meeting is rescheduled to 3 PM tomorrow.
# Korean Query
Q: ν”„λ‘œμ νŠΈ λ―ΈνŒ…μ΄ μ–Έμ œλ‘œ λ³€κ²½λ˜μ—ˆλ‚˜μš”?
A: 내일 μ˜€ν›„ 3μ‹œλ‘œ λ³€κ²½λ˜μ—ˆμŠ΅λ‹ˆλ‹€.
```
## Limitations
- The model is specifically trained for email-related queries
- Performance might vary between English and Korean
- Optimal results when used with email content in standard format
- Limited to the capabilities of the base Qwen model
## Citation
```bibtex
@misc{qwen-rag-lora,
author = {doubleyyh},
title = {Qwen-RAG-LoRA: Fine-tuned LoRA Weights for Email QA},
year = {2024},
publisher = {Hugging Face}
}
```
## License
This model follows the same license as Qwen2.5-7B-Instruct.