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README.md
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@@ -30,15 +30,22 @@ The environmental-claims model is fine-tuned using the EnvironmentalClaims datas
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# Usage
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loading the model :
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from happytransformer import HappyTextClassification
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happy_class = HappyTextClassification(model_type="BERT", model_name="Vinoth24/environmental_claims")
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prediction :
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result = happy_class.classify_text('The reduction of carbon emissions is improving for the last 2 years.')
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print(result) -- TextClassificationResult(label='LABEL_1', score=0.9948860359191895)
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print(result.label) -- LABEL_1
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print(result.score) -- 0.994
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Feel free to train the model more with your custom Environmental claims data. Any queries will be answered. Thank you! :)
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# Usage
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### loading the model :
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```python
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from happytransformer import HappyTextClassification
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happy_class = HappyTextClassification(model_type="BERT", model_name="Vinoth24/environmental_claims")
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```
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### prediction :
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```python
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result = happy_class.classify_text('The reduction of carbon emissions is improving for the last 2 years.')
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print(result) -- TextClassificationResult(label='LABEL_1', score=0.9948860359191895)
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print(result.label) -- LABEL_1
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print(result.score) -- 0.994
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```
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### Result Interpretation:
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LABEL_1 - Related to Environmental Claims
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LABEL_0 - Not Related to Environmental Claims
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Feel free to train the model more with your custom Environmental claims data. Any queries will be answered. Thank you! :)
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