| | import streamlit as st |
| | from transformers import AutoTokenizer, AutoModelForCausalLM |
| | import torch |
| |
|
| | st.title("Uzmi GPT - Romantic Quote Generator") |
| |
|
| | @st.cache_resource |
| | def load_model(): |
| | tokenizer = AutoTokenizer.from_pretrained("rajan3208/uzmi-gpt") |
| | model = AutoModelForCausalLM.from_pretrained("rajan3208/uzmi-gpt") |
| | return tokenizer, model |
| |
|
| | tokenizer, model = load_model() |
| |
|
| | prompt = st.text_area("Enter a prompt", "A romantic quote about forever") |
| |
|
| | if st.button("Generate"): |
| | inputs = tokenizer(prompt, return_tensors="pt") |
| | output = model.generate(**inputs, max_new_tokens=50) |
| | generated = tokenizer.decode(output[0], skip_special_tokens=True) |
| | st.success(generated) |
| |
|
