| # My Toxicity Debiaser Pipeline | |
| This custom pipeline debiases toxic text using a toxicity classifier and GPT-2. | |
| ## Usage | |
| To use this pipeline, you first need to download the required models and tokenizers, and then import the `MyToxicityDebiaserPipeline` class: | |
| ```python | |
| from transformers import AutoTokenizer, AutoModelForSequenceClassification, GPT2LMHeadModel, GPT2Tokenizer | |
| from my_toxicity_debiaser import MyToxicityDebiaserPipeline | |
| toxicity_model_name = "shainaraza/toxity_classify_debiaser" | |
| gpt_model_name = "gpt2" | |
| toxicity_tokenizer = AutoTokenizer.from_pretrained(toxicity_model_name) | |
| toxicity_model = AutoModelForSequenceClassification.from_pretrained(toxicity_model_name) | |
| gpt_tokenizer = GPT2Tokenizer.from_pretrained(gpt_model_name) | |
| gpt_model = GPT2LMHeadModel.from_pretrained(gpt_model_name) | |
| pipeline = MyToxicityDebiaserPipeline( | |
| model=toxicity_model, | |
| tokenizer=toxicity_tokenizer, | |
| gpt_model=gpt_model, | |
| gpt_tokenizer=gpt_tokenizer, | |
| ) | |
| text = "Your example text here" | |
| result = pipeline(text) | |
| print(result) | |