| # {mrp/simcse-model-wangchanberta} | |
| This is a [sentence-transformers](https://www.SBERT.net) 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](https://arxiv.org/pdf/2104.08821.pdf) by using mBERT as the baseline model and training the model with Thai Wikipedia [here](https://github.com/PyThaiNLP/ThaiWiki-clean/releases/tag/20210620?fbclid=IwAR1YcmZkb-xd1ibTWCJOcu98_FQ5x3ioZaGW1ME-VHy9fAQLhEr5tXTJygA) | |
| ## Usage (Sentence-Transformers) | |
| Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) 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) | |
| ``` |