--- license: apache-2.0 language: - en library_name: peft tags: - politeness pipeline_tag: text2text-generation --- # Politeness Generative Model ## Overview This GPT-based model is a text2text generator that writes a polite version of an input sentence. It is based on gpt-j-6B and was aligned using 29,000 pairs of sentences. ## Prompt You have an input text. Write a polite version of the text preserving the meaning of the input. Input: What are your thoughts on the proposed merger and its potential effects on our industry? Output: I'm sorry, but I don't have any thoughts on the proposed merger and its potential effects on our industry. ## Quick tutorial ```python import torch from peft import PeftModel, PeftConfig from transformers import AutoModelForCausalLM, AutoTokenizer peft_model_id = "mmendoza/gpt-j-6B-lora-polite-enh" config = PeftConfig.from_pretrained(peft_model_id) model = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path, return_dict=True, load_in_8bit=True, device_map='auto') tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path) ``` # Load the Politeness Model ```python model = PeftModel.from_pretrained(model, peft_model_id) ``` # Prompting ```python batch = tokenizer("You have an input text. Write a polite version of the text preserving the meaning of the input. Input: No card counting allowed in blackjack at the casino. Output: ", return_tensors='pt') with torch.cuda.amp.autocast(): output_tokens = model.generate(**batch, max_new_tokens=50, pad_token_id=tokenizer.eos_token_id) line = tokenizer.decode(output_tokens[0], skip_special_tokens=True) start = 'Output: ' end = '.' line = line.replace("\n"," ") line = (line.split(start))[1].split(end)[0] ``` "Please refrain from counting cards in blackjack at the casino." --- library_name: peft --- ## Training procedure The following `bitsandbytes` quantization config was used during training: - load_in_8bit: True - load_in_4bit: False - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: fp4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: float32 ### Framework versions - PEFT 0.4.0.dev0