How to use from the
Use from the
sentence-transformers library
from sentence_transformers import SentenceTransformer

model = SentenceTransformer("mrp/simcse-model-roberta-base-thai")

sentences = [
    "That is a happy person",
    "That is a happy dog",
    "That is a very happy person",
    "Today is a sunny day"
]
embeddings = model.encode(sentences)

similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4]

{mrp/simcse-model-roberta-base-thai}

This is a sentence-transformers by using XLM-R as the baseline model 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 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)
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Paper for mrp/simcse-model-roberta-base-thai