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README.md
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@@ -57,8 +57,8 @@ Easiest use with `transformers` and `pipeline`:
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
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model = AutoModelForSequenceClassification.from_pretrained('RJuro/
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tokenizer = AutoTokenizer.from_pretrained('RJuro/
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classifier = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
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@@ -72,7 +72,7 @@ classifier('jeg elsker dig')
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```python
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from simpletransformers.classification import MultiLabelClassificationModel
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model = MultiLabelClassificationModel('bert', 'RJuro/
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predictions, raw_outputs = model.predict(df['text'])
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```
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
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model = AutoModelForSequenceClassification.from_pretrained('RJuro/Da-HyggeBERT')
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tokenizer = AutoTokenizer.from_pretrained('RJuro/Da-HyggeBERT')
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classifier = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
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```python
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from simpletransformers.classification import MultiLabelClassificationModel
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model = MultiLabelClassificationModel('bert', 'RJuro/Da-HyggeBERT')
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predictions, raw_outputs = model.predict(df['text'])
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```
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