---
library_name: transformers
tags:
- knowledge graph
- rag
- gnn
base_model: NousResearch/Hermes-3-Llama-3.1-8B
---

# Model Card for Model ID

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This repository is created for submission to Compfest: Artificial Intelligence Challenge (AIC) 16.

G-Retriever integrates Graph Neural Networks (GNN), Large Language Model (LLM), and Retrieval-Augmented Generation(RAG) by using Knowledge Graph. This model was originaly developed by Xiaoxin He.

## Model Details

### Model Description

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While the original method utilized Llama 2 family model as the LLM, this repository has experimented it with Llama 3.1 8B.

### Model Sources

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- **Repository:** [Repository](https://github.com/alfiannajih/job-recommender) 
- **Training Script:** [G-Retriever Repository](https://github.com/XiaoxinHe/G-Retriever)
- **Paper:** [G-Retriever Paper](https://arxiv.org/abs/2402.07630)

## Uses

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This model is designed to be used as a resume reviewer. The approach involves retrieving a subgraph from a knowledge graph built from LinkedIn job postings and feeding it into a GNN. The features extracted from the subgraph are further processed and concatenated with the input embeddings from the query text. These concatenated features are then passed through the self-attention layer of Llama 3.1 8B to generate a resume review.