| from transformers import T5ForConditionalGeneration, T5Tokenizer | |
| from googletrans import Translator | |
| class GOTSummarizer: | |
| def __init__(self): | |
| self.model = T5ForConditionalGeneration.from_pretrained("yourusername/got_summarizer") | |
| self.tokenizer = T5Tokenizer.from_pretrained("yourusername/got_summarizer") | |
| self.translator = Translator() | |
| def summarize(self, text, max_length=150): | |
| inputs = self.tokenizer("summarize: " + text, return_tensors="pt", truncation=True) | |
| outputs = self.model.generate(**inputs, max_length=max_length) | |
| return self.tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| def translate(self, text, lang='hi'): | |
| return self.translator.translate(text, dest=lang).text |