updated readme
Browse files
README.md
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@@ -35,7 +35,7 @@ import torch
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model = AutoModelForSequenceClassification.from_pretrained("aveluth/author_regulatory_focus_classifier")
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tokenizer = AutoTokenizer.from_pretrained("aveluth/author_regulatory_focus_classifier")
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text = ""
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inputs = tokenizer(text, return_tensors="pt")
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outputs = model(**inputs)
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predicted_class = torch.argmax(outputs.logits).item()
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@@ -43,8 +43,6 @@ predicted_class = torch.argmax(outputs.logits).item()
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print("Predicted class:", "prevention" if predicted_class == 0 else "promotion")
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```
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> Make sure to replace `"your-username/..."` with the correct model path.
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## Labels
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| Class | Description |
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@@ -83,4 +81,4 @@ If you use this model in your research, please cite:
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number={1},
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year={2023}
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}
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```
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model = AutoModelForSequenceClassification.from_pretrained("aveluth/author_regulatory_focus_classifier")
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tokenizer = AutoTokenizer.from_pretrained("aveluth/author_regulatory_focus_classifier")
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text = "Wir müssen sicherstellen, dass keine Fehler passieren. Sicherheit hat höchste Priorität."
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inputs = tokenizer(text, return_tensors="pt")
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outputs = model(**inputs)
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predicted_class = torch.argmax(outputs.logits).item()
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print("Predicted class:", "prevention" if predicted_class == 0 else "promotion")
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```
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## Labels
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| Class | Description |
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number={1},
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year={2023}
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}
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```
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