🚀 sup-simcse-ja-base

sup-simcse-ja-base 是一个用于句子特征提取和相似度计算的模型，它基于预训练的日语 BERT 模型进行微调，能有效处理日语句子的语义理解任务。

🚀 快速开始

📦 安装指南

如果你已经安装了 sentence-transformers，使用该模型会变得非常简单：

pip install -U fugashi[unidic-lite] sentence-transformers

💻 使用示例

基础用法（Sentence-Transformers）

from sentence_transformers import SentenceTransformer
sentences = ["こんにちは、世界！", "文埋め込み最高！文埋め込み最高と叫びなさい", "極度乾燥しなさい"]

model = SentenceTransformer("cl-nagoya/sup-simcse-ja-base")
embeddings = model.encode(sentences)
print(embeddings)

高级用法（HuggingFace Transformers）

若未安装 sentence-transformers，可以按以下方式使用该模型：首先，将输入数据传入 Transformer 模型，然后对上下文词嵌入应用合适的池化操作。

from transformers import AutoTokenizer, AutoModel
import torch


def cls_pooling(model_output, attention_mask):
    return model_output[0][:,0]


# Sentences we want sentence embeddings for
sentences = ['This is an example sentence', 'Each sentence is converted']

# Load model from HuggingFace Hub
tokenizer = AutoTokenizer.from_pretrained("cl-nagoya/sup-simcse-ja-base")
model = AutoModel.from_pretrained("cl-nagoya/sup-simcse-ja-base")

# Tokenize sentences
encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')

# Compute token embeddings
with torch.no_grad():
    model_output = model(**encoded_input)

# Perform pooling. In this case, cls pooling.
sentence_embeddings = cls_pooling(model_output, encoded_input['attention_mask'])

print("Sentence embeddings:")
print(sentence_embeddings)

📚 详细文档

🔧 技术细节

完整模型架构

SentenceTransformer(
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
)

模型概要

更多详细的实验设置请参考 GitHub 仓库。

📄 许可证

本模型采用 CC BY-SA 4.0 许可证。

🔖 引用与作者

@misc{
  hayato-tsukagoshi-2023-simple-simcse-ja,
  author = {Hayato Tsukagoshi},
  title = {Japanese Simple-SimCSE},
  year = {2023},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/hppRC/simple-simcse-ja}}
}