|
|
| import streamlit as st |
| from transformers import pipeline |
|
|
| |
| st.set_page_config( |
| page_title="AI Text Generator", |
| page_icon="🤖", |
| layout="centered" |
| ) |
|
|
| |
| st.title("Dawar Shariq | Student ID: B04-0923-000022") |
| st.header("AI Text Generator") |
|
|
| st.write( |
| "Enter any starting text and let the AI generate " |
| "a continuation using a pretrained Hugging Face model." |
| ) |
|
|
| |
| MODEL_NAME = "distilgpt2" |
|
|
|
|
| |
| @st.cache_resource |
| def load_model(): |
| return pipeline( |
| "text-generation", |
| model=MODEL_NAME |
| ) |
|
|
|
|
| |
| with st.spinner("Loading AI model..."): |
| generator = load_model() |
|
|
| st.success(f"Model loaded: {MODEL_NAME}") |
|
|
| |
| prompt = st.text_area( |
| "Enter your starting text:", |
| placeholder="Example: Artificial intelligence can help people...", |
| height=120 |
| ) |
|
|
| |
| max_new_tokens = st.slider( |
| "Maximum new tokens", |
| min_value=10, |
| max_value=200, |
| value=50, |
| step=10 |
| ) |
|
|
| |
| if st.button("Generate Text", type="primary"): |
|
|
| |
| if not prompt.strip(): |
| st.warning("Please enter some text before generating.") |
|
|
| else: |
| try: |
| with st.spinner("Generating text..."): |
| result = generator( |
| prompt, |
| max_new_tokens=max_new_tokens, |
| num_return_sequences=1, |
| do_sample=True, |
| temperature=0.8, |
| pad_token_id=generator.tokenizer.eos_token_id |
| ) |
|
|
| generated_text = result[0]["generated_text"] |
|
|
| |
| continuation = generated_text[len(prompt):].strip() |
|
|
| st.subheader("Generated Continuation") |
|
|
| if continuation: |
| st.write(continuation) |
| else: |
| st.write(generated_text) |
|
|
| except Exception as error: |
| st.error(f"Something went wrong: {error}") |
|
|
| |
| with st.expander("About this application"): |
| st.write("**Model:** distilgpt2") |
| st.write("**Task:** Text generation") |
| st.write("**Framework:** Hugging Face Transformers") |
| st.write("**Interface:** Streamlit") |
|
|
