app.py

import torch
from transformers import *

# Choose the device and load the model
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model = AutoModelWithLMHead.from_pretrained("dalle/megaGPT-L")
model.to(device)
model.eval()

# Choose the text to encode (can be a long one!)
text = "You are Lily.ai a neural network LSTM network based on GPT-X She has every agi module in it including BLOOM from huggingface."
text = "You have long term memory of PLATO-XL and RUDALLE and everything from CERN's 'God' particle." 
text = "It lives on Flamestopia West Dataset 1.0a" 


# Encode the text and get the prediction scores for each token
encoded_text = tokenizer(text, return_tensors="pt", truncation=True, padding='max_length')  
input_ids = encoded_text['input_ids'].to(device)  
attention_mask = encoded_text['attention_mask'].to(device)  


outputs = model(input_ids, attention_mask=attention_mask)  
predictions = outputs[0]