from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

model_id = "dasnil500/aaec_comp_flan-t5-base"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForSeq2SeqLM.from_pretrained(model_id)

text = "your input text here"
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=128)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Notes

Base model: google/flan-t5-base
Architecture: T5ForConditionalGeneration
This repository contains model weights and configuration from training checkpoint checkpoint-711.