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