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mrp/simcse-model-distil-m-bert
simcse-model-distil-m-bert is a sentence similarity model from mrp. Use it when you need a score for how close two texts are. It is set up for sentence-transformers.
This is a sentence-transformers by using m-Distil-BERT 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.
Downloads · 30 days
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From the Hugging Face model README
This is a sentence-transformers by using m-Distil-BERT 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.
<!--- Describe your model here -->We use SimCSE here and training the model with Thai Wikipedia here
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)