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--- |
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language: "en" |
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thumbnail: "https://huggingface.co/sampathkethineedi" |
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tags: |
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- distilbert |
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- pytorch |
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- tensorflow |
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- text-classification |
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- industry |
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- buisiness |
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- description |
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- multi-class |
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- classification |
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liscence: "mit" |
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inference: false |
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--- |
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# industry-classification |
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## Model description |
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DistilBERT Model to classify a business description into one of **62 industry tags**. |
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Trained on 7000 samples of Business Descriptions and associated labels of companies in India. |
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## How to use |
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PyTorch and TF models available |
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```python |
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from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline |
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tokenizer = AutoTokenizer.from_pretrained("sampathkethineedi/industry-classification") |
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model = AutoModelForSequenceClassification.from_pretrained("sampathkethineedi/industry-classification") |
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industry_tags = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer) |
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industry_tags("Stellar Capital Services Limited is an India-based non-banking financial company ... loan against property, management consultancy, personal loans and unsecured loans.") |
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'''Ouput''' |
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[{'label': 'Consumer Finance', 'score': 0.9841355681419373}] |
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``` |
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## Limitations and bias |
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Training data is only for Indian companies |
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