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import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer

# ื˜ืขื™ื ืช ื”ืžื•ื“ืœ ื•ื”-tokenizer
model = AutoModelForCausalLM.from_pretrained("distilgpt2")
tokenizer = AutoTokenizer.from_pretrained("distilgpt2")

# ืคื•ื ืงืฆื™ื” ืฉืžืงื‘ืœืช ืคืจื•ืžืคื˜ ื•ืžื—ื–ื™ืจื” ืชื’ื•ื‘ื”
def generate_text(prompt):
    inputs = tokenizer(prompt, return_tensors="pt")
    gen_tokens = model.generate(
        inputs.input_ids,
        attention_mask=inputs.attention_mask,
        do_sample=True,
        temperature=0.9,
        max_length=100,
        pad_token_id=tokenizer.eos_token_id
    )
    gen_text = tokenizer.decode(gen_tokens[0], skip_special_tokens=True)
    return gen_text

# ื™ืฆื™ืจืช ืžืžืฉืง Gradio ืขื ืงืœื˜ ืฉืœ ื˜ืงืกื˜ ื•ืคืœื˜ ืฉืœ ื˜ืงืกื˜
iface = gr.Interface(fn=generate_text, inputs="text", outputs="text")

# ื”ืคืขืœืช ื”ืืคืœื™ืงืฆื™ื”
iface.launch()