bert4vector 0.0.5

an elegant bert4vector

bert4vector

向量计算、存储、检索、相似度计算

Documentation | Bert4torch | Examples | Source code

1. 下载安装

• 安装稳定版

pip install bert4vector

• 安装最新版

pip install git+https://github.com/Tongjilibo/bert4vector

2. 快速使用

• 向量计算

from bert4vector.core import BertSimilarity
model = BertSimilarity('/data/pretrain_ckpt/simbert/sushen@simbert_chinese_tiny')
sentences = ['喜欢打篮球的男生喜欢什么样的女生', '西安下雪了？是不是很冷啊?', '第一次去见女朋友父母该如何表现？', '小蝌蚪找妈妈怎么样', '给我推荐一款红色的车', '我喜欢北京']
vecs = model.encode(sentences, convert_to_numpy=True, normalize_embeddings=False)
print(vecs.shape)
# (6, 312)

• 相似度计算

from bert4vector.core import BertSimilarity
text2vec = BertSimilarity('/data/pretrain_ckpt/simbert/sushen@simbert_chinese_tiny')
sent1 = ['你好', '天气不错']
sent2 = ['你好啊', '天气很好']
similarity = text2vec.similarity(sent1, sent2)
print(similarity)
# [[0.9075422  0.42991278]
#  [0.19584633 0.72635853]]

• 向量存储和检索

from bert4vector.core import BertSimilarity
model = BertSimilarity('/data/pretrain_ckpt/simbert/sushen@simbert_chinese_tiny')
model.add_corpus(['你好', '我选你', '天气不错', '人很好看'])
print(model.search('你好'))
# {'你好': [{'corpus_id': 0, 'score': 0.9999, 'text': '你好'},
#           {'corpus_id': 3, 'score': 0.5694, 'text': '人很好看'}]} 

• api部署

from bert4vector.pipelines import SimilaritySever
server = SimilaritySever('/data/pretrain_ckpt/embedding/BAAI--bge-base-zh-v1.5')
server.run(port=port)
# 接口调用可以参考'./examples/api.py'

3. 支持的句向量权重

模型分类	模型名称	权重来源	权重链接	备注(若有)
simbert	simbert	追一科技	Tongjilibo/simbert-chinese-base, Tongjilibo/simbert-chinese-small, Tongjilibo/simbert-chinese-tiny
	simbert_v2/roformer-sim	追一科技	junnyu/roformer_chinese_sim_char_base，junnyu/roformer_chinese_sim_char_ft_base，junnyu/roformer_chinese_sim_char_small，junnyu/roformer_chinese_sim_char_ft_small	roformer_chinese_sim_char_base, roformer_chinese_sim_char_ft_base, roformer_chinese_sim_char_small, roformer_chinese_sim_char_ft_small
embedding	text2vec-base-chinese	shibing624	shibing624/text2vec-base-chinese	text2vec-base-chinese
	m3e	moka-ai	moka-ai/m3e-base	m3e-base
	bge	BAAI	BAAI/bge-large-en-v1.5, BAAI/bge-large-zh-v1.5, BAAI/bge-base-en-v1.5, BAAI/bge-base-zh-v1.5, BAAI/bge-small-en-v1.5, BAAI/bge-small-zh-v1.5	bge-large-en-v1.5, bge-large-zh-v1.5, bge-base-en-v1.5, bge-base-zh-v1.5, bge-small-en-v1.5, bge-small-zh-v1.5
	gte	thenlper	thenlper/gte-large-zh, thenlper/gte-base-zh	gte-base-zh, gte-large-zh

*注：

1. 高亮格式(如Tongjilibo/simbert-chinese-small)的表示可直接联网下载
2. 国内镜像网站加速下载
   • HF_ENDPOINT=https://hf-mirror.com python your_script.py
   • export HF_ENDPOINT=https://hf-mirror.com后再执行python代码
   • 在python代码开头如下设置

   import os
   os.environ['HF_ENDPOINT'] = "https://hf-mirror.com"
   

4. 版本历史

更新日期	bert4vector	版本说明
20240928	0.0.5	小修改，api中可以reset
20240710	0.0.4	增加最长公共子序列字面召回，不安装torch也可以使用部分功能
20240628	0.0.3	增加多种字面召回，增加api接口部署

5. 更新历史：

• 20240928：小修改，api中可以reset
• 20240710：增加最长公共子序列字面召回，不安装torch也可以使用部分功能
• 20240628：增加多种字面召回，增加api接口部署

6. Reference

• similarities
• bert4vec