from transformers import pipeline pipe = pipeline("text-generation", model="THUDM/LongWriter-llama3.1-8b") result = pipe("Write a 10000-word China travel guide") print(result) from transformers import AutoTokenizer, AutoModelForCausalLM import torch tokenizer = AutoTokenizer.from_pretrained("THUDM/LongWriter-llama3.1-8b", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("THUDM/LongWriter-llama3.1-8b", torch_dtype=torch.bfloat16, trust_remote_code=True, device_map="auto") model = model.eval() query = "Write a 10000-word China travel guide" prompt = f"[INST] {query} [/INST]" input = tokenizer(prompt, truncation=False, return_tensors="pt").to(device) context_length = input.input_ids.shape[-1] output = model.generate(**input, max_new_tokens=32768, num_beams=1, do_sample=True, temperature=0.5)[0] response = tokenizer.decode(output[context_length:], skip_special_tokens=True) print(response)