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README.md
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@@ -31,9 +31,8 @@ nfqa_model = RobertaNFQAClassification.from_pretrained("Lurunchik/nf-cats")
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nfqa_tokenizer = AutoTokenizer.from_pretrained("deepset/roberta-base-squad2")
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```
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##### Make prediction using helper function
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```python
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def get_nfqa_category_prediction(text):
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output = nfqa_model(**nfqa_tokenizer(text, return_tensors="pt"))
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index = output.logits.argmax()
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@@ -44,6 +43,12 @@ get_nfqa_category_prediction('how to assign category?')
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#'INSTRUCTION'
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```
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## Citation
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If you use `NFQA-cats` in your work, please cite [this paper](https://dl.acm.org/doi/10.1145/3477495.3531926)
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nfqa_tokenizer = AutoTokenizer.from_pretrained("deepset/roberta-base-squad2")
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```
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##### Make prediction using helper function:
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```python
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def get_nfqa_category_prediction(text):
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output = nfqa_model(**nfqa_tokenizer(text, return_tensors="pt"))
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index = output.logits.argmax()
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#'INSTRUCTION'
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```
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## Demo
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You can test the model via [hugginface space](https://huggingface.co/spaces/Lurunchik/nf-cats).
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[![demo.png](demo.png)](https://huggingface.co/spaces/Lurunchik/nf-cats)
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## Citation
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If you use `NFQA-cats` in your work, please cite [this paper](https://dl.acm.org/doi/10.1145/3477495.3531926)
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demo.png
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