Using Lora to train opt-6.7b import torch from peft import PeftModel, PeftConfig from transformers import AutoModelForCausalLM, AutoTokenizer
peft_model_id = "sayril007/opt_lora-7b-lora-pretrained" config = PeftConfig.from_pretrained(peft_model_id) model = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path, return_dict=True, load_in_8bit=True, device_map='auto') tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)
Load the Lora model
model = PeftModel.from_pretrained(model, peft_model_id)
batch = tokenizer("Two things are infinite: ", return_tensors='pt')
with torch.cuda.amp.autocast(): output_tokens = model.generate(**batch, max_new_tokens=50)
print('\n\n', tokenizer.decode(output_tokens[0], skip_special_tokens=True))