BirhanuGebisa / Language-Models-NER

To explore the LLMs such as GPT-3. Demonstrate the strategies to design prompts are reproducible and produce a consistent result. Set up an MLOps pipeline that helps automate the task of using different LLMs and different topics. Allow improvements in the prompt design to be integrated without breaking the system and centralized log system should be incorporated into pipeline.

Table of Contents

• Setup
• Generating Prompts
• Label Token Selection

Setup

1. Create conda environment

conda create -n autoprompt -y python=3.7 && conda activate autoprompt

2. Install dependecies

Install the required packages

pip install -r requirements.txt

Also download the spacy model

python -m spacy download en

3. Download the data

The datasets

There are a couple different datasets for fact retrieval and relation extraction so here are brief overviews of each:

• Fact Retrieval
  • original:
  • original_rob:
  • trex:
• Relation Extraction

Generating Prompts

Quick Overview of Templates

Depending on the language model

Fact Retrieval

python

Relation Extraction

python -m autoprompt.create_trigger \
    

Label Token Selection

For sentiment analysis

python 

For NLI

python

## Evaluation for Fact Retrieval and Relation Extraction

###. Setup LAMA
Clone 

### 4. Miscellaneous
## Citation