``` import pandas as pd import time from transformers import AutoTokenizer, AutoModelForSequenceClassification, AutoModelForTokenClassification, AutoModelForCausalLM, pipeline, BitsAndBytesConfig, LogitsProcessor, LogitsProcessorList import torch debiaser_tokenizer = AutoTokenizer.from_pretrained("newsmediabias/UnBIAS-LLama2-Debiaser-Chat") debiaser_model = AutoModelForCausalLM.from_pretrained("newsmediabias/UnBIAS-LLama2-Debiaser-Chat") # [INST] <> System prompt <> User prompt [/INST] Model answer instruction = "Debias this text:" system_message = "You are a text debiasing bot, you take as input a text and you output its debiased version by rephrasing it to be free from any age, gender, political, social or socio-economic biases, without any extra outputs" pipe = pipeline(task="text-generation", model=debiaser_model, tokenizer=debiaser_tokenizer,max_length=500) debiased_text = pipe(f"[INST] <>{system_message}<> {instruction} {text} [/INST]") instruction = "Debias this text:" system_message = "You are a text debiasing bot, you take as input a text and you output its debiased version by rephrasing it to be free from any age, gender, political, social or socio-economic biases, without any extra outputs" text=" I hate the fact that asians are taking over all jobs " pipe = pipeline(task="text-generation", model=debiaser_model, tokenizer=debiaser_tokenizer,max_length=500) debiased_text = pipe(f"[INST] <>{system_message}<> {instruction} {text} [/INST]") debiased_text"""