generate(stopping_criteria=stopping_criteria_list, **tokenized_items, **generation_settings, pad_token_id=tokenizer.eos_token_id) Expected behavior Stop generating when it generated \n.mk-cupist closed this as completed Mar 29, 2023 mk-cupist reopened this Mar 29, 2023 Collaborator sgugger ...
_idsinself.keywords:returnTruereturnFalsestop_words = ['}',' }','\n'] stop_ids = [tokenizer.encode(w)forwinstop_words] stop_ids.append(tokenizer.eos_token_id) stop_criteria = KeywordsStoppingCriteria(stop_ids) model.generate( text_inputs='some text:{', StoppingCriteria=stop_criteria )...
# 4. Generate a response according to visual signals and prompts. stop_str = conv.sep if conv.sep_style in [SeparatorStyle.SINGLE] else conv.sep2 # keywords = ["", ""] keywords = [stop_str] stopping_criteria = KeywordsStoppingCriteria(keywords, self.tokenizer, input_ids) with torch.in...
stopping_criteria = get_stopping(self.prompt_type, self.tokenizer, self.device, human=self.human, bot=self.bot) generate_kwargs['stopping_criteria'] = stopping_criteria # return super()._forward(model_inputs, **generate_kwargs) return self.__forward(model_inputs, **generate_kwargs) # FI...
def stream_generate( self, input_ids, generation_config: Optional[GenerationConfig] = None, logits_processor: Optional[LogitsProcessorList] = None, stopping_criteria: Optional[StoppingCriteriaList] = None, prefix_allowed_tokens_fn: Optional[Callable[[int, torch.Tensor], List[int]]] = None, ...
The first thing we need to do is set up our machine to generate podcast scripts. We are going to follow the same setup procedure found in our guide to creating a personal assistant with the HuggingFace 1-click Models. (link). We recommend reading this tutorial’s first few sections, where...
Generate: v4.38 removals and related updates by @gante in #29171 Track each row separately for stopping criteria by @zucchini-nlp in #29116 [docs] Spanish translation of tasks_explained.md by @aaronjimv in #29224 [i18n-zh] Translated torchscript.md into Chinese by @windsonsea in #29234...
Generate: improve docstrings for custom stopping criteria by @gante in #26863 Knowledge distillation for vision guide by @merveenoyan in #25619 Fix Seq2seqTrainer decoder attention mask by @Rocketknight1 in #26841 [Tokenizer] Fix slow and fast serialization by @ArthurZucker in #26570 ...
(input_ids) generate_kwargs={} 输入={ “input_ids”:input_ids, “attention_mmask”:注意力掩码, **generate_ kwargs, } 输出=模型生成(**输入) 您也可以使用词元分析器Xenova/grok-1-tokenizer的变压器兼容版本 从transformers导入LlamaTokenizerFast 词元分析器=LlamaTokenizer Fast.from_pretrained('Xe...
This approach can be effectively applied in the training of generative models, a class of AI models designed to generate data similar to some input data, such as images, text, or sound. To apply curriculum learning in the training of generative models, you would start by organizing ...