Spaces:
Sleeping
Sleeping
import streamlit as st | |
from transformers import AutoTokenizer, AutoModelForCausalLM | |
# Load the tokenizer and model | |
tokenizer = AutoTokenizer.from_pretrained("arabic-text-stanceEvalV1") | |
model = AutoModelForCausalLM.from_pretrained("arabic-text-stanceEvalV1") | |
def generate_text(prompt, max_length=50): | |
inputs = tokenizer(prompt, return_tensors="pt") | |
outputs = model.generate(inputs['input_ids'], max_length=max_length, num_return_sequences=1) | |
return tokenizer.decode(outputs[0], skip_special_tokens=True) | |
st.title("SatnceEval LLM testing with Hugging Face and Streamlit") | |
prompt = st.text_input("Enter your prompt:", "Once upon a time") | |
if st.button("Generate"): | |
with st.spinner("Generating..."): | |
generated_text = generate_text(prompt) | |
st.success("Generated Text:") | |
st.write(generated_text) | |