Instructions to use timonziegenbein/appropriateness-classifier-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use timonziegenbein/appropriateness-classifier-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="timonziegenbein/appropriateness-classifier-binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("timonziegenbein/appropriateness-classifier-binary") model = AutoModelForSequenceClassification.from_pretrained("timonziegenbein/appropriateness-classifier-binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -41,9 +41,8 @@ argument = ''''Towed three times and impounded for 30 days each time? Man, you'r
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out = pipe(argument)
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# LABEL_1 = Inappropriate
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print(out)
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#[{'label': 'LABEL_1', 'score': 0.9970095157623291}]
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```
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## Citation
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out = pipe(argument)
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print(out)
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# [{'label': 'LABEL_1', 'score': 0.9970095157623291}] = Inappropriate
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```
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## Citation
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