app.py

import streamlit as st
from transformers import GPT2LMHeadModel, GPT2Tokenizer

@st.cache(allow_output_mutation=True)
def load_model():
    MODEL_NAME = "gpt2"  # Ändern Sie dies entsprechend
    tokenizer = GPT2Tokenizer.from_pretrained(MODEL_NAME)
    model = GPT2LMHeadModel.from_pretrained(MODEL_NAME)
    return model, tokenizer

def generate_text(prompt, model, tokenizer):
    inputs = tokenizer.encode(prompt, return_tensors="pt")
    outputs = model.generate(inputs, max_length=200, num_return_sequences=5)
    generated_text = [tokenizer.decode(output) for output in outputs]
    return generated_text

model, tokenizer = load_model()

st.title("Textgenerierung mit GPT-2")
prompt = st.text_input("Geben Sie einen Prompt ein:")
if prompt:
    with st.spinner("Generieren von Text..."):
        generated_text = generate_text(prompt, model, tokenizer)
    st.header("Generierter Text:")
    for i, text in enumerate(generated_text):
        st.subheader(f"Option {i+1}:")
        st.write(text)