from transformers import AutoModelForCausalLM, AutoTokenizer model_id = "KrushnaVardhanReddy/PaperPilot-Qwen-0.5B-Instruct"tokenizer = AutoTokenizer.from_pretrained(model_id)model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto") messages = [ { "role": "system", "content": "You are PaperPilot's on-device neural assistant. Convert user instructions into strict JSON tool calls. For single operations, emit a single JSON object. For multi-step workflows, emit a JSON array of tool calls chained in execution order." }, { "role": "user", "content": "Combine document1.pdf and document2.pdf into merged.pdf and then compress it." }] text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)inputs = tokenizer([text], return_tensors="pt").to(model.device)outputs = model.generate(**inputs, max_new_tokens=256, do_sample=False)print(tokenizer.decode(outputs[0][len(inputs.input_ids[0]):], skip_special_tokens=True))