repetition_penalty(float, optional, defaults to 1.0) — The parameter for repetition penalty. 1.0 means no penalty. See this paper for more details. repetition_penalty:默认是1.0,重复词惩罚。 论文:CTRL: A CONDITIONAL TRANSFORMER LANGUAGE MODEL FOR CONTROLLABLE GENERATION pad_token_id(int, optional)...
encoder_repetition_penalty (`float`, *optional*, defaults to 1.0): The paramater for encoder_repetition_penalty. An exponential penalty on sequences that are not in the original input. 1.0 means no penalty. length_penalty (`float`, *optional*, defaults to 1.0): Exponential penalty to the l...
diversity_penalty (浮点数,可选,默认为 0.0): 如果生成的某个时间点的令牌与同一组其他束的令牌相同,将从束的分数中减去 diversity_penalty。请注意,只有当 group beam search 启用时,diversity_penalty 才有效。 repetition_penalty (浮点数,可选,默认为 1.0): 重复惩罚参数。1.0 表示没有惩罚。有关更多详细信...
{ 'max_length': 512, 'max_new_tokens': None, 'num_beams': 1, 'do_sample': False, 'use_past': True, 'temperature': 1.0, 'top_k': 0, 'top_p': 1.0, 'repetition_penalty': 1.0, 'encoder_repetition_penalty': 1.0, 'renormalize_logits': False, 'pad_token_id': 2, 'bos_token...
# "repetition_penalty":1.3, } generate_ids = model.generate(**generate_input) content = tokenizer.decode(generate_ids[0]) return content print(invoke4(model,tokenizer,'你好')) generate结果: 你好,我是一名大学生。寒假期间在一家快餐店工作。因为一些原因,我只工作了十天。我和老板口头约定工资1200元...
repetition_penalty = args.repetition_penalty device = "cuda" if torch.cuda.is_available() else "cpu" tokenizer = BertTokenizer(vocab_file=args.tokenizer_path) model_config = GPT2Config.from_json_file(args.model_config) model = GPT2LMHeadModel(config=model_config) state_dict = torch.load(...
{'max_length': 1024, 'max_new_tokens': None, 'min_length': 0, 'min_new_tokens': None, 'num_beams': 1, 'do_sample': False, 'use_past': True, 'temperature': 0.7, 'top_k': 0, 'top_p': 1.0, 'repetition_penalty': 1.3, 'encoder_repetition_penalty': 1.0, 'renormalize_...
[`~generation.GenerationMixin.contrastive_search`]if`penalty_alpha>0.`and`top_k>1`-*multinomial sampling*by calling[`~generation.GenerationMixin.sample`]if`num_beams=1`and`do_sample=True`-*beam-search decoding*by calling[`~generation.GenerationMixin.beam_search`]if`num_beams>1`and`do_sample...
请问什么版本的paddleNLP啊，看起来是input_spec传错了？
repetition_penalty: float = 1.0, length_penalty: float = 1.0, no_repeat_ngram_size: int = 0, **kwargs **kwargs, ): """Generate text from the given prompt.@@ -80,7 +80,7 @@ def generate(self, prompts: Union[str, List[str]], **kwargs): ...