Description
Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. industry-classification
is a English model originally trained by sampathkethineedi
.
Predicted Entities
Semiconductors
, Data Processing & Outsourced Services
, Oil & Gas Exploration & Production
, Industrial Machinery
, Technology Distributors
, Apparel Retail
, Application Software
, Research & Consulting Services
, Specialty Stores
, Diversified Support Services
, Gold
, Human Resource & Employment Services
, Interactive Media & Services
, Internet & Direct Marketing Retail
, Auto Parts & Equipment
, Building Products
, Personal Products
, Communications Equipment
, Electronic Equipment & Instruments
, Regional Banks
, Systems Software
, Health Care Services
, Health Care Supplies
, Asset Management & Custody Banks
, Aerospace & Defense
, Specialty Chemicals
, Life Sciences Tools & Services
, Electric Utilities
, Commodity Chemicals
, Health Care Equipment
, Technology Hardware, Storage & Peripherals
, Construction Machinery & Heavy Trucks
, Environmental & Facilities Services
, Oil & Gas Equipment & Services
, Oil & Gas Refining & Marketing
, Casinos & Gaming
, Diversified Metals & Mining
, Property & Casualty Insurance
, Hotels, Resorts & Cruise Lines
, IT Consulting & Other Services
, Leisure Products
, Pharmaceuticals
, Movies & Entertainment
, Restaurants
, Steel
, Thrifts & Mortgage Finance
, Health Care Facilities
, Oil & Gas Storage & Transportation
, Internet Services & Infrastructure
, Health Care Technology
, Packaged Foods & Meats
, Integrated Telecommunication Services
, Consumer Finance
, Investment Banking & Brokerage
, Electrical Components & Equipment
, Trading Companies & Distributors
, Construction & Engineering
, Advertising
, Homebuilding
, Biotechnology
, Real Estate Operating Companies
, Apparel, Accessories & Luxury Goods
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
sequenceClassifier_loaded = DistilBertForSequenceClassification.pretrained("distilbert_sequence_classifier_industry_classification","en") \
.setInputCols(["document", "token"]) \
.setOutputCol("class")
pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded])
data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
result = pipeline.fit(data).transform(data)
val documentAssembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val tokenizer = new Tokenizer()
.setInputCols(Array("document"))
.setOutputCol("token")
val sequenceClassifier_loaded = DistilBertForSequenceClassification.pretrained("distilbert_sequence_classifier_industry_classification","en")
.setInputCols(Array("document", "token"))
.setOutputCol("class")
val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded))
val data = Seq("PUT YOUR STRING HERE").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("en.classify.distil_bert.by_sampathkethineedi").predict("""PUT YOUR STRING HERE""")
Model Information
Model Name: | distilbert_sequence_classifier_industry_classification |
Compatibility: | Spark NLP 4.1.0+ |
License: | Open Source |
Edition: | Official |
Input Labels: | [document, token] |
Output Labels: | [ner] |
Language: | en |
Size: | 249.9 MB |
Case sensitive: | true |
Max sentence length: | 128 |
References
- https://huggingface.co/sampathkethineedi/industry-classification