Simcse Model M Bert Thai Cased

🚀 {kornwtp/simcse-model-m-bert-thai-cased}

This is a sentence-transformers model that maps sentences and paragraphs to a 768-dimensional dense vector space, which can be used for tasks such as clustering or semantic search.

🚀 Quick Start

This is a sentence-transformers model. It maps sentences and paragraphs to a 768-dimensional dense vector space and can be applied to tasks like clustering or semantic search.

We utilize SimCSE here, with mBERT as the baseline model, and train the model using Thai Wikipedia here

📦 Installation

Using this model becomes easy when you have sentence-transformers installed:

pip install -U sentence-transformers

💻 Usage Examples

Basic Usage

from sentence_transformers import SentenceTransformer
sentences = ["กลุ่มผู้ชายเล่นฟุตบอลบนชายหาด", "กลุ่มเด็กชายกำลังเล่นฟุตบอลบนชายหาด"]

model = SentenceTransformer('{MODEL_NAME}')
embeddings = model.encode(sentences)
print(embeddings)

📄 License

This project is licensed under the Apache-2.0 license.