Instructions to use Unggi/hate_speech_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Unggi/hate_speech_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Unggi/hate_speech_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Unggi/hate_speech_bert") model = AutoModelForSequenceClassification.from_pretrained("Unggi/hate_speech_bert") - Notebooks
- Google Colab
- Kaggle
Upload BertForSequenceClassification
Browse files- config.json +3 -3
- pytorch_model.bin +1 -1
config.json
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "
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"1": "
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "hate",
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"1": "none",
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"2": "offensive"
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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pytorch_model.bin
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size 368829557
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