model = AutoModelForCausalLM.from_pretrained( model_name, device_map="auto", torch_dtype=torch.float16, load_in_4bit=True # Critical for MoE memory savings )
prompt = "Explain the significance of the Dragon God in Shinto mythology." inputs = tokenizer(prompt, return_tensors="pt").to("cuda") outputs = model.generate(**inputs, max_new_tokens=512) print(tokenizer.decode(outputs[0], skip_special_tokens=True)) ryujin 3.5
For developers, the lesson is clear: The era of dense LLMs is sunsetting. Have you run an MoE model locally? How does your experience compare to dense models like LLaMA? Share your benchmarks in the comments below. model = AutoModelForCausalLM
