
# Sentence BERT fine-tuned commodities
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

## how to cite
```
@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.} 
}
```

## how to use
```
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-months-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']))
```
{"license": "mit"}
transformers pytorch distilbert feature-extraction license:mit endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #feature-extraction #license-mit #endpoints_compatible #region-us 


# Sentence BERT fine-tuned commodities
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: URL

## how to cite


## how to use

# Sentence BERT fine-tuned commodities
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: URL ## how to cite ## how to use
TAGS
#transformers #pytorch #distilbert #feature-extraction #license-mit #endpoints_compatible #region-us 
 # Sentence BERT fine-tuned commodities
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: URL ## how to cite ## how to use