Skip to content

Latest commit

 

History

History

NE

Folders and files

NameName
Last commit message
Last commit date

parent directory

..
main.py
main.py
 
 
prompts.py
prompts.py
 
 
readme.md
readme.md
 
 
test.py
test.py
 
 
utils.py
utils.py
 
 

readme.md

Number Extraction with Large Language Models (NE Subtask)

Important Update

Note: The gpt-3.5-turbo-0613 model is deprecated and replaced with gpt-3.5-turbo. Consequently, results obtained using gpt-3.5-turbo may differ from those reported in earlier experiments using gpt-3.5-turbo-0613.

Installation

  1. Clone the repository:
git clone https://github.com/HLR/BLInD.git
cd BLInD
  1. Install the required dependencies:
python -m pip install --upgrade pip
pip install -r requirements.txt
cd GG

API Keys Setup

For using the models, you'll need to obtain the necessary API keys:

  • For OpenAI models (gpt-3.5-turbo, gpt-4-0613): Get your API key from OpenAI
  • For other models (Meta LLaMA, Mistral): Get your API key from Replicate

Usage

To query LLMs for GG, use the main.py script:

python main.py [--testdataset TESTDATASET] [--outputdataset OUTPUTDATASET] 
[--openaikey OPENAIKEY] [--openaiorg OPENAIORG] [--replicatekey REPLICATEKEY]
[--samplenum SAMPLENUM] [--models MODEL [MODEL ...]] [--maxattempt MAXATTEMPT] 
[--reversed]

Arguments

  • --testdataset: Input test dataset (default: "../datasets/Colored_1000_examples.csv")
  • --outputdataset: Dataset folder to save the results (default: "../datasets/")
  • --openaikey: OpenAI API key
  • --openaiorg: OpenAI organization key
  • --replicatekey: Replicate.ai API key (required for non-OpenAI models)
  • --samplenum: Number of instances of the dataset to read (default: 2000)
  • --models: Choose one or more models from:
    • gpt-3.5-turbo
    • gpt-4-0613
    • meta/meta-llama-3-70b-instruct
    • mistralai/mistral-7b-instruct-v0.2
    • meta/llama-2-70b-chat
  • --maxattempt: Max number of attempts after a failed prompt (default: 10)
  • --reversed: Whether to reverse the order of operations by including the graph first (default: False)

This program saves every answer after each prompt. If it terminates, run it again, and it will pick up where it left off. This code also tries different combinations of NE and GG together.

Testing LLMs for Bayesian Inference

To test LLMs for GG, use the test.py script:

python test.py [--testdataset TESTDATASET] [--outputdataset OUTPUTDATASET]
[--models MODEL [MODEL ...]] [--reversed]

Test Arguments

  • --testdataset: Input test dataset (default: "../datasets/Colored_1000_examples.csv")
  • --outputdataset: Dataset folder that has saved the results (default: "../datasets/")
  • --models: Choose one or more models (same choices as main.py)
  • --reversed: Whether to reverse the order of operations by including the graph first (default: False)

Dataset

The code uses a test dataset specified by the --testdataset argument. By default, it uses the "../datasets/Colored_1000_examples.csv" dataset.

Models

The code supports various language models through different APIs:

OpenAI Models

  • gpt-3.5-turbo
  • gpt-4-0613

Replicate.ai Models

  • meta/meta-llama-3-70b-instruct
  • mistralai/mistral-7b-instruct-v0.2
  • meta/llama-2-70b-chat

Output

The results of running Bayesian inference are saved in the dataset folder specified by the --outputdataset argument. The output files are named based on the arguments set in main.py.