apply_chat_template( messages, tokenize=False ) print(new_prompt) 使用apply_chat_template 方法将聊天消息转换为模型输入格式。 4.3 获取实际词汇表长度 actual_vocab_size = len(tokenizer) print('tokenizer实际词表长度:', actual_vocab_size) 4.4 编码和解码 model_inputs = tokenizer(new_prompt) print(...
调用tokenizer.apply_chat_template()时,可以传入add_generation_prompt=True使得该脚本最后的判断为真。 准本好 json 对话chat,就可以使用tokenizer.apply_chat_template(chat, tokenize=False)看一下模板生成效果。 tokenizer.apply_chat_template(chat, tokenize=False)# <bos><start_of_turn>user\n1+1等于几?<e...
要解决 "cannot use apply_chat_template() because tokenizer.chat_template is not set" 的问题,您可以按照以下步骤进行: 1. 确认 tokenizer 对象是否已正确初始化 确保您已经正确加载了 tokenizer 对象。通常,这是通过 AutoTokenizer.from_pretrained() 方法完成的,如下所示: python from transformers import Auto...
For a lot of tokenizers in Tokenizer.apply_chat_template with continue_final_message=True we get a "ValueError: substring not found" if the final message starts or ends in some whitespace. Here is ...
const tokens = tokenizer.apply_chat_template( [ { role: "system", content: "你是一个有趣的ai助手", }, { role: "user", content: "好好,请问怎么去月球?", }, ] ) as number[]; // 转化成token的数组 console.log(tokens); const chat_content = tokenizer.decode(tokens); // 还原了的...
import { fromPreTrained } from "@lenml/tokenizer-llama3";const tokenizer = fromPreTrained();const tokens = tokenizer.apply_chat_template([{role: "system",content: "你是一个有趣的ai助手",},{role: "user",content: "好好,请问怎么去月球?",},]) as number[];// 转化成token的数组console....
Added the option to use the tokenizer default chat template of the base model (the one loaded from tokenizer_config.json of the base model). This was done by adding an entry to thetemplatesdict, where the key is"tokenizer"and the value isNone. Whentokenizer.apply_chat_templateis called wi...
import{fromPreTrained}from"@lenml/tokenizer-llama3";consttokenizer=fromPreTrained(); chat template consttokens=tokenizer.apply_chat_template([{role:"system",content:"You are helpful assistant.",},{role:"user",content:"Hello, how are you?",},])asnumber[];constchat_content=tokenizer.decode(tok...
chat_templete 也沿用了 DeepSeek 的模版 补充:Qwen 本身 base 和 instruct 模型相比基本一致,除了 instruct 模型在 chat_template 里的默认 system 里加了“You are Qwen, created by Alibaba Cloud. ”。 先看下Qwen 的 chat 模版: {%-iftools%}{{-'<|im_start|>system\n'}}{%-ifmessages[0]['role...
hf_chat_template ... True hidden_dropout ... 0.0 hidden_size ... 4096 hysteresis ... 2 ict_head_size ... None ict_load ...