| import gradio as gr | |
| from transformers import pipeline, set_seed | |
| from transformers import GPTNeoForCausalLM, GPT2Tokenizer | |
| model = GPTNeoForCausalLM.from_pretrained("EleutherAI/gpt-neo-1.3B") | |
| tokenizer = GPT2Tokenizer.from_pretrained("EleutherAI/gpt-neo-1.3B") | |
| set_seed(42) | |
| def Bemenet(bemenet): | |
| input_ids = tokenizer(bemenet, return_tensors="pt").input_ids | |
| gen_tokens = model.generate( | |
| input_ids, | |
| do_sample=True, | |
| temperature=0.9, | |
| max_length=100, | |
| ) | |
| return tokenizer.batch_decode(gen_tokens)[0] | |
| interface = gr.Interface(fn=Bemenet, | |
| title="Cím..", | |
| description="Leírás..", | |
| inputs="text", | |
| outputs="text") | |
| interface.launch() |