This is a converted XLM‑RoBERTa large model using CLS pooling for embeddings. It’s not trained yet, but it can be effectively trained to make a cool embedding model
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FacebookAI/xlm-roberta-large
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Parveshiiii/Embedding") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3]