pad_token = tokenizer.eos_token # add a padding token tokenizer.padding_side = 'right' # to prevent warnings # LoRA config based on QLoRA paper & Sebastian Raschka experiment peft_config = LoraConfig( lora_alpha=128, lora_dropout=0.05, r=256, bias="none", target_modules="all-linear",...
使用Hugging Face的transformers库,我们可以通过方法“add_special_tokens”来实现这一点。 tokenizer.add_special_tokens({'pad_token': '[PAD]'}) input = tokenizer(prompts, padding='max_length', max_length=20, return_tensors="pt"); print(input) Output: {'input_ids': tensor([[32000, 32000, ...
使用model_name, AutoTokenizer可以下载该标记器。 在第36行,调用add_special_tokens({' pad_token ': ' [PAD] '})这是另一个重要代码,因为我们数据集中的文本长度可以变化,批处理中的序列可能具有不同的长度。为了确保批处理中的所有序列具有相同的长度,需要将填充令牌添加到较短的序列中。这些填充标记通常是...
device_map='auto', torch_dtype=torch.float16, load_in_8bit=True)#加载模型model = model.eval()#切换到eval模式tokenizer = AutoTokenizer.from_pretrained(Path(f'{pretrained_model_name_or_path}'), use_fast=False)#加载tokenizertokenizer.pad_token = tokenizer...
tokenizer.pad_token = tokenizer.eos_token #为了防止生成的文本出现[PAD],这里将[PAD]重置为[EOS]input_ids = tokenizer(['Human: 介绍一下中国\nAssistant: '], return_tensors="pt", add_special_tokens=False).input_ids.to('cuda') #将输入的文本转换为tokengenerate_input = { "input_ids": inpu...
tokenizer.pad_token = tokenizer.eos_token input_ids = tokenizer(['Human: 介绍一下中国\nAssistant: '], return_tensors="pt",add_special_tokens=False).input_ids.to('cuda') generate_input = {"input_ids":input_ids,"max_new_tokens":512,"do_sample":True,"top_k":50,"top_p":0.95,"te...
tokenizer.pad_token = tokenizer.eos_token input_ids = tokenizer(['Human: 介绍一下中国\nAssistant: '], return_tensors="pt",add_special_tokens=False).input_ids.to('cuda') generate_input = {"input_ids":input_ids,"max_new_tokens":512,"do_sample":True,"top_k":50,"top_p":0.95,"te...
input_ids, batch_first=True, padding_value=self.tokenizer.pad_token_id ) labels = torch.nn.utils.rnn.pad_sequence(labels, batch_first=True, padding_value=-100) return dict( input_ids=input_ids, labels=labels, attention_mask=input_ids.ne(self.tokenizer.pad_token_id), ...
pad_token = tokenizer.eos_token input_ids = tokenizer(['Human: 介绍一下中国\nAssistant: '], return_tensors="pt",add_special_tokens=False).input_ids.to('cuda') generate_input = { "input_ids":input_ids, "max_new_tokens":512, "do_sample":True, "top_k":50, "top_p":0.95, "te...
DEFAULT_PAD_TOKEN = "[PAD]" DEFAULT_EOS_TOKEN = "" DEFAULT_BOS_TOKEN = "" DEFAULT_UNK_TOKEN = "<unk>" @dataclass class ModelArguments: model_name_or_path: Optional[str] = field( default=None, metadata={ "help": (...