要执行此操作,需再次将model_id作为参数传递给AutoTokenizer类的.from_pretrained方法。 请注意,本例中还使用了其他一些参数,但当前而言,理解它们并不重要,因此我们不会解释它们。 tokenizer = AutoTokenizer.from_pretrained(model_id, add_eos_token=True, padding_side='left') 分词器是什么? 分词器负责将句子分...
tokenizer.tokenize('lemonade') # ['▁le', 'mon', 'ade'] .encode(str | list or tokens) 只做单个句子的转编码(要么是字符串,要么是token列表,要么是id列表(用来添加special token)),控制参数几乎和tokenizer()相同,比如可以指定add_special_tokens,默认是True. 可以代替tokenizer(),因为大多数时候我们只...
model = AutoModelForCausalLMWithValueHead.from_pretrained(config.model_name) tokenizer = AutoTokenizer.from_pretrained(config.model_name) tokenizer.pad_token = tokenizer.eos_token #Defining the reward model deep_hub reward_model = pipeline("text-classification",model="lvwerra/distilbert-imdb") def ...
frankfliu requested review from zachgk and a team as code owners January 22, 2024 23:52 siddvenk approved these changes Jan 22, 2024 View reviewed changes frankfliu mentioned this pull request Jan 22, 2024 Add get methods for HuggingFaceTokenizer fields #2956 Closed codecov-commenter co...
初始化一个tokenizer 和 model,这里使用的是Bert进行 定义一段 text 和几个 question 对question 列表遍历,将每个question都和text 组成一个sequence 将sequence 扔到模型中,模型为 sequence 中每个 token (包括text和question)都输出两个score,代表这个位置是答案开始和结束位置的分数。 对分数计算softmax 生成概率 ...
tokenizer.pad_token = tokenizer.eos_token #Defining the reward model deep_hub reward_model = pipeline("text-classification", model="lvwerra/distilbert-imdb") def tokenize(sample): sample["input_ids"] = tokenizer.encode(sample["query"]) ...
from_pretrained("huggyllama/llama-7b", add_eos_token=True, from_slow=True) This will produce the expected outputs: >>> fast.encode("auto_tokenizer", add_special_tokens = True) [1, 4469, 29918, 6979, 3950, 2] The reason behind this is that the post_processor is responsible of adding...
trainer = RewardTrainer(model=model,args=training_args,tokenizer=tokenizer,train_dataset=dataset,peft_config=peft_config, ) trainer.train() RLHF微调(用于对齐) 在这一步中,我们将从第1步开始训练SFT模型,生成最大化奖励模型分数的输出。具体来说就是将使用奖励模型来调整监督模型的输出,使其产生类似人类的...
让huggingface/transformers的AutoTokenizer从本地读词表 https://stackoverflow.com/questions/62472238/autotokenizer-from-pretrained-fails-to-load-locally-saved-pretrained-tokenizer
--model-type GPT \ --loader llama2_hf \ --saver megatron \ --target-tensor-parallel-size 1 \ --target-pipeline-parallel-size 2 \ --load-dir ./model_from_hf/llama-2-7b-hf/ \ --save-dir ./model_weights/llama-2-7b-hf-v0.1-tp8-pp1/ \ --tokenizer-model ./model_from_hf/lla...