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1import torch
2from peft import PeftModel, PeftConfig
3from transformers import AutoModelForCausalLM, AutoTokenizer
4
5peft_model_id = "Yooko/gpt3-finnish-small-ft-AbirateEN"
6config = PeftConfig.from_pretrained(peft_model_id)
7model = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path, return_dict=True, load_in_8bit=True, device_map='auto')
8tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)
9
10# Load the Lora model
11model = PeftModel.from_pretrained(model, peft_model_id)1batch = tokenizer("Two things are infinite: ", return_tensors='pt')
2
3with torch.cuda.amp.autocast():
4 output_tokens = model.generate(**batch, max_new_tokens=50)
5
6print('\n\n', tokenizer.decode(output_tokens[0], skip_special_tokens=True))