kornwtp/ConGen-simcse-model-roberta-base-thai
This is a ConGen model: It maps sentences to a 768 dimensional dense vector space and can be used for tasks like semantic search.
Usage
Using this model becomes easy when you have ConGen installed:
pip install -U git+https://github.com/KornWtp/ConGen.git
Then you can use the model like this:
from sentence_transformers import SentenceTransformer
sentences = ["กลุ่มผู้ชายเล่นฟุตบอลบนชายหาด", "กลุ่มเด็กชายกำลังเล่นฟุตบอลบนชายหาด"]
model = SentenceTransformer('kornwtp/ConGen-simcse-model-roberta-base-thai')
embeddings = model.encode(sentences)
print(embeddings)
Evaluation Results
For an automated evaluation of this model, see the Thai Sentence Embeddings Benchmark: Semantic Textual Similarity
Citing & Authors
@inproceedings{limkonchotiwat-etal-2022-congen,
title = "{ConGen}: Unsupervised Control and Generalization Distillation For Sentence Representation",
author = "Limkonchotiwat, Peerat and
Ponwitayarat, Wuttikorn and
Lowphansirikul, Lalita and
Udomcharoenchaikit, Can and
Chuangsuwanich, Ekapol and
Nutanong, Sarana",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2022",
year = "2022",
publisher = "Association for Computational Linguistics",
}
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