| import gradio as gr | |
| from transformers import AutoTokenizer, GPTJForCausalLM | |
| model_name = "rycont/kakaobrain__kogpt-6b-8bit" | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = GPTJForCausalLM.from_pretrained(model_name) | |
| def generate_response(prompt): | |
| inputs = tokenizer(prompt, return_tensors="pt") | |
| outputs = model.generate(inputs['input_ids'], max_new_tokens=50) | |
| response = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| return response | |
| iface = gr.Interface( | |
| fn=generate_response, | |
| inputs="text", | |
| outputs="text", | |
| title="KoGPT-6B Chatbot", | |
| description="Enter a prompt and the model will generate a response." | |
| ) | |
| if __name__ == "__main__": | |
| iface.launch() | |