Text Classification
Transformers
PyTorch
Safetensors
xlm-roberta
Cross-lingual-nlp
zero-shot-transfer
toxicity-analysis
abuse-detection
flag-user
block-user
multilinguality
XLM-R
Instructions to use Jayveersinh-Raj/PolyGuard with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jayveersinh-Raj/PolyGuard with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jayveersinh-Raj/PolyGuard")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jayveersinh-Raj/PolyGuard") model = AutoModelForSequenceClassification.from_pretrained("Jayveersinh-Raj/PolyGuard") - Notebooks
- Google Colab
- Kaggle
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#### Preprocessing
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We merged all the sub categories of toxicity to create a super category of toxicity, since all of them are severe, flaggable, and/or blockable.
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Class imbalance was present, but state of the art transformer architecture can handle it well.
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#### Preprocessing
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We merged all the sub categories of toxicity to create a super category of toxicity, since all of them are severe, flaggable, and/or blockable.
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Class imbalance was present, but state of the art transformer architecture can handle it well.
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