Nuance in usage of GPT2 when setting the attribute trainable
gpt2 = GPT2LMHeadModel.from_pretrained(‘gpt2’, cache_dir=“./cache”, local_files_only=True)gpt2.trainable = Falsegpt2.config.pad_token_id=50256gen_nlp  = pipeline(“text-generation”, model=gpt2, tokenizer=tokenizer_gpt2, device=args.gpu, return_full_text=False)contents = ds.df_train.sample(10)[‘content’].tolist()results_trunk = gen_nlp(contents, max_length=64, do_sample=True, top_p=0.9, top_k=0,repetition_penalty=1.0, num_return_sequences=4, clean_up_tokenization_spaces=True)I use off-the-shelf GPT2 for open-ended generation. I find that there is a parametertrainablewhich needs to be set False or True before using.Anyone know the nuance in this setting?What is the best setting for this parameter?Thanks.