Instructions to use Sakil/distilbert_lazylearner_hatespeech_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sakil/distilbert_lazylearner_hatespeech_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sakil/distilbert_lazylearner_hatespeech_detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sakil/distilbert_lazylearner_hatespeech_detection") model = AutoModelForSequenceClassification.from_pretrained("Sakil/distilbert_lazylearner_hatespeech_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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* Different strategies have been followed during the data gathering phase.
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* The dataset is collected from relevant sources.
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# distilbert-base-uncased model is fine-tuned for Hate Speech Detection
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* The model is fine-tuned on the dataset.
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* This model can be used to create the labels for academic purposes or for industrial purposes.
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* This model can be used for the inference purpose as well.
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* Different strategies have been followed during the data gathering phase.
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* The dataset is collected from relevant sources.
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# distilbert-base-uncased model is fine-tuned for Hate Speech Detection
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* The model is fine-tuned on the dataset.
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* This model can be used to create the labels for academic purposes or for industrial purposes.
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* This model can be used for the inference purpose as well.
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