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1import torch
2device = torch.device("cuda")
3tokenizer = ByteLevelBPETokenizer.from_pretrained("just-ne-just/llm-course-hw1")
4model = TransformerForCausalLM.from_pretrained("just-ne-just/llm-course-hw1")
5model = model.to(device)
6model = model.eval()
7
8text = "Купил мужик шляпу"
9input_ids = torch.tensor(tokenizer.encode(text), device=device)
10model_output = model.generate(
11 input_ids[None, :], max_new_tokens=50, eos_token_id=tokenizer.eos_token_id, do_sample=True, top_k=10
12)
13tokenizer.decode(model_output[0].tolist())