code: def load_sst_sentiment_explainability():
      print("Loading Sst-sentiment-explainability dataset")
  
      # Load dataset from json
      my_dataframe = pd.read_json(
          "https://raw.githubusercontent.com/recognai/datasets/main/sst-sentimentclassification.json"
      )
  
      # Convert pandas dataframe to DatasetForTextClassification
      dataset_rg = rg.DatasetForTextClassification.from_pandas(
          my_dataframe
      )
  
      # Define labeling schema to avoid UI user modification
      settings = rg.TextClassificationSettings(
          label_schema={"POSITIVE", "NEGATIVE"}
      )
      rg.configure_dataset(
          name="sst-sentiment-explainability", settings=settings
      )
  
      # Log the dataset
      rg.log(
          dataset_rg,
          name="sst-sentiment-explainability",
          tags={
              "description": "The sst2 sentiment dataset with predictions from a pretrained pipeline and "
              "explanations from Transformers Interpret."
          },
      )
  
file_path: argilla/docker/scripts/load_data.py
imports: import sys
  import time
  from typing import Union
  import argilla
  import pandas
  import requests
  from argilla.labeling.text_classification import Rule, add_rules
  from datasets import load_dataset
label_desc: Use image node_id 3 for calling the LoadDatasets obj's underlying member method code with example usage: obj.load_sst_sentiment_explainability() without return types