| T5 Model for Formality Style Transfer. Trained on the GYAFC dataset. | |
| PyTorch model available. | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
| | |
| tokenizer = AutoTokenizer.from_pretrained("Isotonic/informal_to_formal") | |
| model = AutoModelForSeq2SeqLM.from_pretrained("Isotonic/informal_to_formal") | |
| | |
| sentence = "will you look into these two deals and let me know" | |
| text = "Make the following sentence Formal: " + sentence + " </s>" | |
| encoding = tokenizer.encode_plus(text,pad_to_max_length=True, return_tensors="pt") | |
| input_ids, attention_masks = encoding["input_ids"].to("cuda"), encoding["attention_mask"].to("cuda") | |
| outputs = model.generate( | |
| input_ids=input_ids, attention_mask=attention_masks, | |
| max_length=256, | |
| do_sample=True, | |
| top_k=120, | |
| top_p=0.95, | |
| early_stopping=True, | |
| num_return_sequences=5 | |
| ) | |
| for output in outputs: | |
| line = tokenizer.decode(output, skip_special_tokens=True,clean_up_tokenization_spaces=True) | |
| print(line) | |
| Output: "Would you look into the two deals in question, then let me know?" |