convert_to_sentence_vectors.py

!pip install --quiet sentence_transformers==2.2.0

from sentence_transformers import SentenceTransformer
model= SentenceTransformer('all-MiniLM-L12-v2')

def get_answer_and_distractor_embeddings(answer,candidate_distractors):
  answer_embedding = model.encode([answer])
  distractor_embeddings = model.encode(candidate_distractors)
  return answer_embedding,distractor_embeddings


distractors.insert(0,originalword)
print (distractors)

answer_embedd, distractor_embedds = get_answer_and_distractor_embeddings(originalword,distractors)