| --- |
| license: apache-2.0 |
| pipeline_tag: sentence-similarity |
| tags: |
| - sentence-transformers |
| - feature-extraction |
| - sentence-similarity |
| - transformers |
| --- |
| |
| # {kornwtp/simcse-model-distil-m-bert} |
|
|
| This is a [sentence-transformers](https://www.SBERT.net) 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](https://arxiv.org/pdf/2104.08821.pdf) 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: |
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|
| ```python |
| from sentence_transformers import SentenceTransformer |
| sentences = ["กลุ่มผู้ชายเล่นฟุตบอลบนชายหาด", "กลุ่มเด็กชายกำลังเล่นฟุตบอลบนชายหาด"] |
| |
| model = SentenceTransformer('{MODEL_NAME}') |
| embeddings = model.encode(sentences) |
| print(embeddings) |
| ``` |