pipeline_tag: 特征提取

作者风格表征变换器 - STAR

本仓库用于存放作者风格表征变换器(STAR)模型。我们在此公开模型权重。

欢迎访问我们的STAR GitHub仓库获取复现代码。

特征提取

tokenizer = AutoTokenizer.from_pretrained('roberta-large')
model = AutoModel.from_pretrained('AIDA-UPM/star')

examples = ['我的文本1', '这是另一个文本']

def extract_embeddings(texts):
  encoded_texts = tokenizer(texts)
  with torch.no_grad():
    style_embeddings = model(encoded_texts.input_ids,
                             attention_mask=encoded_texts.attention_mask).pooler_output
  return style_embeddings

print(extract_embeddings(examples))

引用文献

@article{Huertas-Tato2023Oct,
	author = {Huertas-Tato, Javier and Martin, Alejandro and Camacho, David},
	title = {{基于监督对比预训练变换器的社交媒体写作风格理解}},
	journal = {arXiv},
	year = {2023},
	month = oct,
	eprint = {2310.11081},
	doi = {10.48550/arXiv.2310.11081}
}