You can deploy this model and start earning money today!

GagaLey/
MoR

Name: MoR
Availability: InStock

meta-llama/Llama-3.2-3B-Instruct

finetune

mit

endpoints_compatible

Views

No views yet

MoR

This model card for our paper Mixture of Structural-and-Textual Retrieval over Text-rich Graph Knowledge Bases.

Code: https://github.com/Yoega/MoR

Running the Evaluation and Reranking Script

Installation

To set up the environment, you can install dependencies using Conda or pip:

Using Conda

bash

conda env create -f mor_env.yml
conda activate your_env_name  # Replace with actual environment name

Using pip

pip install -r requirements.txt

Inference

To run the inference script, execute the following command in the terminal:

bash eval_mor.sh

This script will automatically process three datasets using the pre-trained planning graph generator and the pre-trained reranker.

Training (Train MoR from Scratch)

Step1: Training the planning graph generator

bash train_planner.sh

Step2: Train mixed traversal to collect candidates (note: there is no training process for reasoning)

bash run_reasoning.sh

Step3: Training the reranker

bash train_reranker.sh

Generating training data of Planner

We provide codes to generate your own training data to finetune the Planner by using different LLMs.

If you are using Azure API

bash

python script.py --model "model_name" \
  --dataset_name "dataset_name" \
  --azure_api_key "your_azure_key" \
  --azure_endpoint "your_azure_endpoint" \
  --azure_api_version "your_azure_version"

If you are using OpenAI API

bash

python script.py --model "model_name" \
  --dataset_name "dataset_name" \
  --openai_api_key "your_openai_key" \
  --openai_endpoint "your_openai_endpoint"

GagaLey/MoR

MoR

Running the Evaluation and Reranking Script

Installation

Using Conda

Using pip

Inference

Training (Train MoR from Scratch)

Step1: Training the planning graph generator

Step2: Train mixed traversal to collect candidates (note: there is no training process for reasoning)

Step3: Training the reranker

Generating training data of Planner

We provide codes to generate your own training data to finetune the Planner by using different LLMs.

If you are using Azure API

If you are using OpenAI API

GagaLey/
MoR