--- license: apache-2.0 --- # K2-Chat: a fully-reproducible large language model outperforming Llama 2 70B using 35% less compute blurb
k2 eval table
k2 big eval table
## Loading K2-Chat ```python from transformers import AutoModelForCausalLM, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("LLM360/K2-Chat") model = AutoModelForCausalLM.from_pretrained("LLM360/K2-Chat") prompt = '<|beginofuser|>what is the highest mountain on earth?<|beginofsystem|>' input_ids = tokenizer(prompt, return_tensors="pt").input_ids gen_tokens = model.generate(input_ids, do_sample=True, max_new_tokens=128) print("-"*20 + "Output for model" + 20 * '-') print(tokenizer.batch_decode(gen_tokens)[0]) ```