27 lines
915 B
Python
27 lines
915 B
Python
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from modelscope import AutoModelForCausalLM, AutoTokenizer
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model_name = "Qwen/Qwen3-4B-Instruct-2507-FP8"
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# load the tokenizer and the model
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype="auto", device_map="auto")
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# prepare the model input
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# prompt = "Give me a short introduction to large language model."
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prompt = "中国的首都在哪里？"
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messages = [{"role": "user", "content": prompt}]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True,
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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# conduct text completion
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generated_ids = model.generate(**model_inputs, max_new_tokens=16384)
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output_ids = generated_ids[0][len(model_inputs.input_ids[0]) :].tolist()
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content = tokenizer.decode(output_ids, skip_special_tokens=True)
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print("content:", content)
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