Instructions to use Hate-speech-CNERG/bert-base-uncased-hatexplain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hate-speech-CNERG/bert-base-uncased-hatexplain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Hate-speech-CNERG/bert-base-uncased-hatexplain")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Hate-speech-CNERG/bert-base-uncased-hatexplain") model = AutoModelForSequenceClassification.from_pretrained("Hate-speech-CNERG/bert-base-uncased-hatexplain") - Inference
- Notebooks
- Google Colab
- Kaggle
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language: en
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license: apache-2.0
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- hatexplain
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The model is used for classifying a text as **Hatespeech**, **Offensive**, or **Normal**. The model is trained using data from Gab and Twitter and *Human Rationales* were included as part of the training data to boost the performance.
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language: en
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license: apache-2.0
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datasets:
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- hatexplain
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The model is used for classifying a text as **Hatespeech**, **Offensive**, or **Normal**. The model is trained using data from Gab and Twitter and *Human Rationales* were included as part of the training data to boost the performance.
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