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

Name: simcse-model-m-bert-thai-cased
Availability: InStock

sentence-transformers

text-embeddings-inference

endpoints_compatible

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{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.

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:

python

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

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