| import gradio as gr | |
| from transformers import pipeline, set_seed | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| checkpoint = "bigcode/starcoder-3b" | |
| device = "cpu" | |
| tokenizer = AutoTokenizer.from_pretrained(checkpoint) | |
| model = AutoModelForCausalLM.from_pretrained(checkpoint).to(device) | |
| generator = pipeline('text-generation', model='gpt2', return_full_text=False) | |
| set_seed(42) | |
| def Bemenet(bemenet): | |
| inputs = tokenizer.encode(bemenet, return_tensors="pt").to(device) | |
| outputs = model.generate(inputs) | |
| return tokenizer.decode(outputs[0]) | |
| interface = gr.Interface(fn=Bemenet, | |
| title="Cím..", | |
| description="Leírás..", | |
| inputs="text", | |
| outputs="text") | |
| interface.launch() |