🍭 Korean sentence embedding repository. You can download the pre-trained models and inference right away, also it provides environments where individuals can train models.
Quick tour
import torch
from transformers import AutoModel, AutoTokenizer
defcal_score(a, b):
iflen(a.shape) == 1: a = a.unsqueeze(0)
iflen(b.shape) == 1: b = b.unsqueeze(0)
a_norm = a / a.norm(dim=1)[:, None]
b_norm = b / b.norm(dim=1)[:, None]
return torch.mm(a_norm, b_norm.transpose(0, 1)) * 100
model = AutoModel.from_pretrained('BM-K/KoSimCSE-roberta')
tokenizer = AutoTokenizer.from_pretrained('BM-K/KoSimCSE-roberta')
sentences = ['치타가 들판을 가로 질러 먹이를 쫓는다.',
'치타 한 마리가 먹이 뒤에서 달리고 있다.',
'원숭이 한 마리가 드럼을 연주한다.']
inputs = tokenizer(sentences, padding=True, truncation=True, return_tensors="pt")
embeddings, _ = model(**inputs, return_dict=False)
score01 = cal_score(embeddings[0][0], embeddings[1][0])
score02 = cal_score(embeddings[0][0], embeddings[2][0])
Performance
Semantic Textual Similarity test set results
Model
AVG
Cosine Pearson
Cosine Spearman
Euclidean Pearson
Euclidean Spearman
Manhattan Pearson
Manhattan Spearman
Dot Pearson
Dot Spearman
KoSBERT
†
SKT
77.40
78.81
78.47
77.68
77.78
77.71
77.83
75.75
75.22
KoSBERT
80.39
82.13
82.25
80.67
80.75
80.69
80.78
77.96
77.90
KoSRoBERTa
81.64
81.20
82.20
81.79
82.34
81.59
82.20
80.62
81.25
KoSentenceBART
77.14
79.71
78.74
78.42
78.02
78.40
78.00
74.24
72.15
KoSentenceT5
77.83
80.87
79.74
80.24
79.36
80.19
79.27
72.81
70.17
KoSimCSE-BERT
†
SKT
81.32
82.12
82.56
81.84
81.63
81.99
81.74
79.55
79.19
KoSimCSE-BERT
83.37
83.22
83.58
83.24
83.60
83.15
83.54
83.13
83.49
KoSimCSE-RoBERTa
83.65
83.60
83.77
83.54
83.76
83.55
83.77
83.55
83.64
KoSimCSE-BERT-multitask
85.71
85.29
86.02
85.63
86.01
85.57
85.97
85.26
85.93
KoSimCSE-RoBERTa-multitask
85.77
85.08
86.12
85.84
86.12
85.83
86.12
85.03
85.99
Runs of BM-K KoSimCSE-roberta on huggingface.co
6.0K
Total runs
1.2K
24-hour runs
1.2K
3-day runs
2.7K
7-day runs
-347
30-day runs
More Information About KoSimCSE-roberta huggingface.co Model
KoSimCSE-roberta huggingface.co
KoSimCSE-roberta huggingface.co is an AI model on huggingface.co that provides KoSimCSE-roberta's model effect (), which can be used instantly with this BM-K KoSimCSE-roberta model. huggingface.co supports a free trial of the KoSimCSE-roberta model, and also provides paid use of the KoSimCSE-roberta. Support call KoSimCSE-roberta model through api, including Node.js, Python, http.
KoSimCSE-roberta huggingface.co is an online trial and call api platform, which integrates KoSimCSE-roberta's modeling effects, including api services, and provides a free online trial of KoSimCSE-roberta, you can try KoSimCSE-roberta online for free by clicking the link below.
BM-K KoSimCSE-roberta online free url in huggingface.co:
KoSimCSE-roberta is an open source model from GitHub that offers a free installation service, and any user can find KoSimCSE-roberta on GitHub to install. At the same time, huggingface.co provides the effect of KoSimCSE-roberta install, users can directly use KoSimCSE-roberta installed effect in huggingface.co for debugging and trial. It also supports api for free installation.