simcse-model-m-bert-thai-cased

{mrp/simcse-model-m-bert-thai-cased}

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

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We use SimCSE here by using mBERT as the baseline model and training the model with Thai Wikipedia here

Usage (Sentence-Transformers)

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

pip install -U sentence-transformers

Then you can use the model like this:

from sentence_transformers import SentenceTransformer
sentences = ["ฉันนะคือคนรักชาติยังไงละ!", "พวกสามกีบล้มเจ้า!"]

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