| from transformers import T5Tokenizer, T5ForConditionalGeneration | |
| def longText(answere, question): | |
| print('###### LANGUAGES ######') | |
| input_text = "i have a question and answer.\nthe question is : {}\n the response is : {}\n with this information, can you create an answer phrase?".format(question, answere) | |
| print(question) | |
| print(answere) | |
| print(input_text) | |
| tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-large") | |
| model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-large") | |
| input_ids = tokenizer(input_text, return_tensors="pt").input_ids | |
| outputs = model.generate(input_ids) | |
| return tokenizer.decode(outputs[0]).replace("<pad>","").replace("</s>","") | |