--- language: en tags: - sentence-transformers - sentence-similarity - transformers pipeline_tag: sentence-similarity --- # recobo/agri-sentence-transformer This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 512 dimensional dense vector space and can be used for tasks like clustering or semantic search. This model was built using [recobo/agriculture-bert-uncased](https://huggingface.co/recobo/agriculture-bert-uncased), which is a BERT model trained on 6.5 million passages from the agricultural domain. Hence, this model is expected to perform well on sentence similarity tasks specifically for agricultural text data. ## 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 = ["A man is eating food.", "A man is eating a piece of bread"] model = SentenceTransformer('recobo/agri-sentence-transformer') embeddings = model.encode(sentences) print(embeddings)