app.py

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

# Load tokenizer and model
tokenizer = AutoTokenizer.from_pretrained("simbolo-ai/Myanmarsar-GPT")
model = AutoModelForCausalLM.from_pretrained("simbolo-ai/Myanmarsar-GPT")

# Move model to GPU if available
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model.to(device)

# Input text
input_text = "Marketing"
input_ids = tokenizer.encode(input_text, return_tensors='pt').to(device)

# Generate output
output = model.generate(
    input_ids,
    max_length=256,
    do_sample=True,
    temperature=0.7,
    top_k=50,
    top_p=0.95
)

# Decode and print
print(tokenizer.decode(output[0], skip_special_tokens=True))