| # cased Finnish Sentence BERT model | |
| Finnish Sentence BERT trained from FinBERT | |
| ## Training | |
| FinBERT model: TurkuNLP/bert-base-finnish-cased-v1 | |
| Data: The data provided [here] (https://turkunlp.org/paraphrase.html), including the Finnish Paraphrase Corpus and the automatically collected paraphrase candidates (500K positive and 5M negative) | |
| Pooling: mean pooling | |
| Task: Binary prediction, whether two sentences are paraphrases or not. Note: the labels 3 and 4 are considered paraphrases, and labels 1 and 2 non-paraphrases. [Details on labels] (https://aclanthology.org/2021.nodalida-main.29/) | |
| ## Usage | |
| Please refer to the [HuggingFace documentation] (https://huggingface.co/sentence-transformers/bert-base-nli-mean-tokens) | |
| Briefly, using the `SentenceTransformer` library, | |
| ``` | |
| from sentence_transformers import SentenceTransformer | |
| sentences = ["Tämä on esimerkkilause.", "Tämä on toinen lause."] | |
| model = SentenceTransformer('sbert-cased-finnish-paraphrase') | |
| embeddings = model.encode(sentences) | |
| print(embeddings) | |
| ``` | |