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sampathkethineedi/industry-classification sampathkethineedi/industry-classification
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pytorch

tf

Contributed by

sampathkethineedi Sampath Kethineedi
3 models

How to use this model directly from the πŸ€—/transformers library:

			
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from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sampathkethineedi/industry-classification") model = AutoModelForSequenceClassification.from_pretrained("sampathkethineedi/industry-classification")
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industry-classification

Model description

DistilBERT Model to classify a business description into one of 62 industry tags. Trained on 7000 samples of Business Descriptions and associated labels of companies in India.

How to use

PyTorch and TF models available

from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline

tokenizer = AutoTokenizer.from_pretrained("sampathkethineedi/industry-classification")  
model = AutoModelForSequenceClassification.from_pretrained("sampathkethineedi/industry-classification")

industry_tags = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer)
industry_tags("Stellar Capital Services Limited is an India-based non-banking financial company ... loan against property, management consultancy, personal loans and unsecured loans.")

'''Ouput'''
[{'label': 'Consumer Finance', 'score': 0.9841355681419373}]

Limitations and bias

Training data is only for Indian companies