length_penalty (浮点数,可选,默认为 1.0): 用于基于束生成的指数惩罚。它作为序列长度的指数使用,进而用于除以序列的分数。因为分数是序列的对数似然(即负数),所以 length_penalty > 0.0 促进较长序列,而 length_penalty < 0.0 鼓励较短序列。 no_repeat_ngram_size (整数,可选,默认为 0): 如果设置大于 0...
forced_eos_token_id (int, optional):达到最大长度max_length时,强制作为最后生成的token id。 remove_invalid_values (bool, optional):是否删除模型nan(not a number)和inf(正无穷)防止崩溃,但可能会减慢生成速度。 exponential_decay_length_penalty (tuple(int, float), optional):生成一定数量的token之后,施...
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 length that is used with beam-based generation. It is applied as an...
length_penalty=generation_config.length_penalty, do_early_stopping=generation_config.early_stopping, num_beam_hyps_to_keep=generation_config.num_return_sequences, num_beam_groups=generation_config.num_beam_groups, max_length=generation_config.max_length, ) # 12. interleave input_ids with `num_bea...
* `length_penalty`:控制生成文本长度的惩罚因子。较小的值将鼓励更长的文本,而较大的值将鼓励更短的文本。 * `early_stopping`:如果为True,则提前停止生成过程,当生成的文本与之前生成的文本相似时。 * `use_cache`:如果为True,则缓存输入ID的转换结果以提高生成速度。 这些参数可以根据需要进行调整,以获得最...
beam_output = model.generate( sample, ... logits_processor_list=logits_processor_list, early_stopping=True, num_return_sequences=k, ... do_sample=False, output_scores=True, return_dict_in_generate=True, length_penalty=0, ) Expected behavior ...
min_length=kwargs.get("min_length", 1), top_p=kwargs.get("top_p", 1.0), repetition_penalty=kwargs.get("repetition_penalty", 1.0), length_penalty=kwargs.get("length_penalty", 1.0), length_penalty=kwargs.get("length_penalty", 0.8), temperature=kwargs.get("temperature", 1.0), atten...
inputs = tokenizer.encode("summarize: " + ARTICLE, return_tensors="pt", max_length=512) outputs = model.generate(inputs, max_length=150, min_length=40, length_penalty=2.0, num_beams=4, early_stopping=True) 1. 2. 3. 4. 5. 6. 7. 6. Translation 翻译任务,该任务的一个数据集例子...
{ '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...
Truss structurePenalty length methodModifying ground structure methodTopology optimizationStructural topology optimization plays an important role in obtaining conceptual designs in the preliminary design stage. However, traditional structural optimization methods can only generate one optimized design for the ...