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paulorvdc/sentencebert-fine-tuned-weeks-corn
sentencebert-fine-tuned-weeks-corn is a feature extraction model from paulorvdc. Use it when you need embeddings to search or compare text. It is set up for transformers. The card lists the license as mit.
This model is part of a collection of fine-tuned Sentence BERT models that were generated with the data of the "TRENCHANT: TRENd PrediCtion on Heterogeneous informAtion NeTworks" article. Source code and networks are…
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From the Hugging Face model README
This model is part of a collection of fine-tuned Sentence BERT models that were generated with the data of the "TRENCHANT: TRENd PrediCtion on Heterogeneous informAtion NeTworks" article. Source code and networks are available at the following GitHub repo: https://github.com/paulorvdc/TRENCHANT
@article{doCarmo_ReisFilho_Marcacini_2023,
title={TRENCHANT: TRENd PrediCtion on Heterogeneous informAtion NeTworks},
volume={13},
url={https://sol.sbc.org.br/journals/index.php/jidm/article/view/2546},
DOI={10.5753/jidm.2022.2546},
number={6},
journal={Journal of Information and Data Management},
author={do Carmo, P. and Reis Filho, I. J. and Marcacini, R.},
year={2023},
month={Jan.}
}
from sentence_transformers import SentenceTransformer, LoggingHandler
import numpy as np
import logging
# load model
np.set_printoptions(threshold=100)
logging.basicConfig(format='%(asctime)s - %(message)s',
datefmt='%Y-%m-%d %H:%M:%S',
level=logging.INFO,
handlers=[LoggingHandler()])
model = SentenceTransformer('paulorvdc/sentencebert-fine-tuned-weeks-corn')
finetuned_embeddings = list(model.encode(['Livestock Producers in Brazil Fear Diversion of Corn to Export and Ethanol Production', 'Brazilian Farmers Undecided about Safrinha Corn Acreage']))