Finance NLP 1.4.0 for Spark NLP has been released!

We are happy to welcome the new 1.4.0 version of Finance NLP, including the following new capabilities.

Spark Ecosystem

Finance NLP has been built on top of Spark NLP, which uses Spark MLLib pipelines. This means, you can have a common pipeline with any component of Spark NLP of Spark MLLib. Also, you combine it with the rest of our licensed libraries, such as Visual NLP, Healthcare NLP or Legal NLP. The library works on the top of Transformers and other Deep Learning architectures, providing state-of-the-art models which can be run on Spark Clusters. Remember, Spark NLP is the only library natively scalable to do parallel computing, so it is Finance NLP.

New Models

Named Entity Recognition

Demo for “finner_contraliability"

• finner_contraliability → This is a financial model to detect LIABILITY and CONTRA_LIABILITY mentioned in texts.
  – CONTRA_LIABILITY: Negative liability account that offsets the liability account (e.g. paying a debt)
  – LIABILITY: Current or Long-Term Liability (not from stockholders)

Improved NER Models : We have an improved version of some NER models, including:

finner_earning_calls_generic_md : This is a md(medium) version of a financial model trained on Earning Calls transcripts to detect financial entities (NER model). This model is called Generic as it has fewer labels in comparison with the Specific version.

We have added 12 new models having 12 entitiees each which have been trained on 10Q reports. These models are a subset of the finner_10q_xlbr which contains a total of 139 entities.
finner_10q_xlbr_md_subset1 , finner_10q_xlbr_md_subset2 , finner_10q_xlbr_md_subset3 , finner_10q_xlbr_md_subset4 , finner_10q_xlbr_md_subset5 , finner_10q_xlbr_md_subset6 , finner_10q_xlbr_md_subset7 , finner_10q_xlbr_md_subset8, finner_10q_xlbr_md_subset9 , finner_10q_xlbr_md_subset10 , finner_10q_xlbr_md_subset11 , finner_10q_xlbr_md_subset12

New Sentence Embeddings

We have released new Chinese and English Bert Sentence embeddings based on Finance Transformers.

sbert_chinese_qmc_finance_v1 , sbert_chinese_qmc_finance_v1_distill , sbert_setfit_finetuned_financial_text_classification

Financial Solution Accelerator

The notebooks for the Company’s Ecosystem Graph solution accelerator have been revamped and renewed, now available at https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL/Finance/databricks_solutions_accelerators/company_ecosystem_graph and ready to use with johnsnowlabs>=4.2.3 in Databricks through Partner Connect!

Docker Webapps to check Finance Zero-shot NER

Do you want to check Zero-shot Finance NER? Use our dockerized webapps for streamlit or flask+jinja2 and learn about prompt engineering, while you speed up the prototyping of your NER models without any training data. Available at https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL/Finance/platforms/docker

Want to see more?

• Check our Models Hub
• Check our Notebooks
• Check our Demos

How to install?

!pip install johnsnowlabs
from johnsnowlabs import *

# Before 4.2.3
jsl.install(json_license_path=[your_finance_license_path])
jsl.start(json_license_path=[your_finance_license_path])# After 4.2.3
nlp.install(json_license_path=[your_finance_license_path])
nlp.start(json_license_path=[your_finance_license_path])

Do you want to get certified in Finance NLP?

We will carry out a Certification training session of 4 hours in Jan, 2023. If you are interested, please check the dates and register here https://www.johnsnowlabs.com/spark-nlp-training/