!pip install finetuner
# coding = utf-8
import os
import torch
import torch_npu

from sentence_transformers import SentenceTransformer
from sentence_transformers.util import cos_sim

import argparse
from openmind import pipeline, is_torch_npu_available

parser = argparse.ArgumentParser(description='manual to this script')
parser.add_argument("--model_name_or_path", type=str, default="./")
args = parser.parse_args()

device None
if is_torch_npu_available():
    device = "npu:0"
else:
    device = "cpu"
# load tokenizer

sentences_1 = ['how is the weather today']
sentences_2 = [ 'What is the current weather like today?']

model = SentenceTransformer(args.model_path)
model = model.to(device)
embeddings = model.encode(['how is the weather today', 'What is the current weather like today?'])

cosine_scores = cos_sim(embeddings[0], embeddings[1])
print(f"cosine_scores: {cosine_scores}")

@misc{günther2023jina,
      title={Jina Embeddings: A Novel Set of High-Performance Sentence Embedding Models}, 
      author={Michael Günther and Louis Milliken and Jonathan Geuter and Georgios Mastrapas and Bo Wang and Han Xiao},
      year={2023},
      eprint={2307.11224},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}