
Note: This model may not perfectly replicate the numbers mentioned in the paper (\cite{chopra-ghosh-2021-term}) as unlike the original one it has been trained with lower batches sizes for fewer epochs.

The source code for training will son be made available in https://github.com/sohomghosh/FinSim_Financial_Hypernym_detection


```bibtex
@inproceedings{chopra-ghosh-2021-term,
    title = "Term Expansion and {F}in{BERT} fine-tuning for Hypernym and Synonym Ranking of Financial Terms",
    author = "Chopra, Ankush  and
      Ghosh, Sohom",
    booktitle = "Proceedings of the Third Workshop on Financial Technology and Natural Language Processing (FinNLP@IJCAI 2021)",
    month = "Aug ",
    year = "2021",
    address = "Online",
    publisher = "-",
    url = "https://aclanthology.org/2021.finnlp-1.8",
    pages = "46--51",
}
```

Use the following code to import this in Transformers:
```python
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("sohomghosh/LIPI_FinSim3_Hypernym")

model = AutoModel.from_pretrained("sohomghosh/LIPI_FinSim3_Hypernym")


#Using SentenceTransformers
from sentence_transformers import SentenceTransformer
model_finlipi = SentenceTransformer('sohomghosh/LIPI_FinSim3_Hypernym')
```
{"license": "mit"}
transformers pytorch bert feature-extraction license:mit endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #bert #feature-extraction #license-mit #endpoints_compatible #has_space #region-us 


Note: This model may not perfectly replicate the numbers mentioned in the paper (\cite{chopra-ghosh-2021-term}) as unlike the original one it has been trained with lower batches sizes for fewer epochs.

The source code for training will son be made available in URL




Use the following code to import this in Transformers:

TAGS
#transformers #pytorch #bert #feature-extraction #license-mit #endpoints_compatible #has_space #region-us 

passage: TAGS
#transformers #pytorch #bert #feature-extraction #license-mit #endpoints_compatible #has_space #region-us 
