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from transformers import AutoModelForCausalLM, AutoTokenizer device = "cuda" # the device to load the model onto
model = AutoModelForCausalLM.from_pretrained( "Qwen/Qwen2-72B-Instruct", torch_dtype="auto", device_map="auto" ) tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2-72B-Instruct")
prompt = "Give me a short introduction to large language model." messages = [ {"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": prompt} ] text = tokenizer.apply_chat_template( messages, tokenize=False, add_generation_prompt=True ) model_inputs = tokenizer([text], return_tensors="pt").to(device)
generated_ids = model.generate( model_inputs.input_ids, max_new_tokens=512 ) generated_ids = [ output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids) ]
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]