README.md

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dialogue-bart-large-chinese

This is a seq2seq model fine-tuned on several Chinese dialogue datasets, from bart-large-chinese.

Datasets

We utilize 4 Chinese dialogue datasets from LUGE

	Count	Domain
Chinese Persona Chat (CPC)	23,000	Open
LCCC	11,987,759	Open
Emotional STC (ESTC)	899,207	Open
KdConv	3,000	Movie, Music, Travel

Example

from transformers import BertTokenizer, BartForConditionalGeneration

# Note that tokenizer is an object of BertTokenizer, instead of BartTokenizer
tokenizer = BertTokenizer.from_pretrained("HIT-TMG/dialogue-bart-large-chinese")
model = BartForConditionalGeneration.from_pretrained("HIT-TMG/dialogue-bart-large-chinese")

# an example from CPC dev data
history = ["可以 认识 一下 吗 ？", "当然 可以 啦 ， 你好 。", "嘿嘿 你好 ， 请问 你 最近 在 忙 什么 呢 ？", "我 最近 养 了 一只 狗狗 ， 我 在 训练 它 呢 。"]
history_str = "历史：" + tokenizer.sep_token.join(history)
input_ids = tokenizer(history_str, return_tensors='pt').input_ids
output_ids = model.generate(input_ids)[0]
print(tokenizer.decode(output_ids))