this is my method, my question is how to access the encoder be sending 2 sentences each time? because I have a dataset that contain pairs of sentences, and I need to compute the similarity between each pair.
//anyone could help?
model = SentenceTransformer('paraphrase-MiniLM-L6-v2')
#Sentences we want to encode. Example:
sentence = ['This framework generates embeddings for each input sentence']
sentence1 = ['This is an embedding for framework generation']
#Sentences are encoded by calling
embedding = model.encode(sentence)
embedding1 = model.encode(sentence1)
e = np.squeeze(np.asarray(embedding))
e1 = np.squeeze(np.asarray(embedding1))
#calculate Cosine Similarity
cos_sim = dot(e, e1)/(norm(e)*norm(e1))
print(cos_sim)
