from transformers import AutoTokenizer, AutoModelForCausalLM model_name = "NousResearch/Hermes-2-Pro-Llama-3-8B" model = AutoModelForCausalLM.from_pretrained(model_name) tokenizer = AutoTokenizer.from_pretrained(model_name) # Example messages input # messages = [ # {"role": "system", "content": "You are Hermes 2."}, # {"role": "user", "content": "Hello, who are you?"} #] def generate(messages): gen_input = tokenizer.apply_chat_template(messages, return_tensors="pt") output_ids = model.generate(**gen_input, num_beams=3, no_repeat_ngram_size=2, max_new_tokens=100, eos_token_id=tokenizer.eos_token_id) return tokenizer.decode(output_ids[0], skip_special_tokens=True)