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import gradio as gr | |
from transformers import AutoTokenizer, AutoModelForCausalLM | |
# Load the model and tokenizer | |
model = AutoModelForCausalLM.from_pretrained("umutbozdag/autotrain-g39vl-h3lir") | |
tokenizer = AutoTokenizer.from_pretrained("umutbozdag/autotrain-g39vl-h3lir") | |
def generate_text(input_text): | |
# Tokenize input and generate text | |
inputs = tokenizer(input_text, return_tensors="pt") | |
outputs = model.generate(**inputs, max_length=100) | |
return tokenizer.decode(outputs[0], skip_special_tokens=True) | |
iface = gr.Interface( | |
fn=generate_text, | |
inputs=gr.Textbox(lines=5, label="Input Text"), | |
outputs=gr.Textbox(label="Generated Text"), | |
title="Text Humanizer", | |
description="Enter text to generate a more human-like version." | |
) | |
iface.launch() |