| 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) | |