| from sentence_transformers import SentenceTransformer | |
| class GetEmbedding: | |
| def __init__(self,data:list): | |
| self.data = data | |
| def user_query_emb(self,model_name:str = 'paraphrase-MiniLM-L6-v2'): | |
| try: | |
| model = SentenceTransformer(model_name_or_path=model_name) | |
| embedding = model.encode(self.data) | |
| return embedding | |
| except Exception as e: | |
| print(e) | |
| def convert_data(self,model_name:str = 'paraphrase-MiniLM-L6-v2'): | |
| try: | |
| model = SentenceTransformer(model_name) | |
| embeddings = model.encode(self.data) | |
| return embeddings | |
| except Exception as e: | |
| print(e) | |
| if __name__ == "__main__": | |
| emb = GetEmbedding("lalit") | |
| print( emb) |