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f66e5f6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | import h5py as h5
import sys
import json
import pandas as pd
import torch
import time
from sentence_transformers import SentenceTransformer
#torch.set_num_threads(32)
D = pd.read_parquet("yahoo-answers/question-answer-pair")
# title, article
modelname = 'sentence-transformers/all-MiniLM-L6-v2'
model = SentenceTransformer(modelname)
print(D.columns)
#print("embeddings title")
#embeddings = model.encode(D.title)
#
#with h5.File("ccnews.h5", "w") as f:
# f["title"] = embeddings
# f.attrs["model"] = modelname
print("computing embeddings")
st = time.time()
embeddings = model.encode(D.question)
print("finished in {}s".format(time.time() - st))
with h5.File("yahoo-question-answer.h5", "a") as f:
f["question"] = embeddings
f.attrs["model"] = modelname
st = time.time()
embeddings = model.encode(D.answer)
print("finished in {}s".format(time.time() - st))
with h5.File("yahoo-question-answer.h5", "a") as f:
f["answer"] = embeddings
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