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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)
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