Instructions to use gplsi/Toxicity_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gplsi/Toxicity_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gplsi/Toxicity_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gplsi/Toxicity_model") model = AutoModelForSequenceClassification.from_pretrained("gplsi/Toxicity_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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## 📌 Model Description
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This model is a fine-tuned version** of `RoBERTa-base-bne`, specifically trained to classify the toxicity level of **Spanish-language user comments on news articles**. It distinguishes between
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- **Non-toxic**
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- **Slightly toxic**
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## 📌 Model Description
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This model is a fine-tuned version** of `RoBERTa-base-bne`, specifically trained to classify the toxicity level of **Spanish-language user comments on news articles**. It distinguishes between three categories:
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- **Non-toxic**
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- **Slightly toxic**
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