Instructions to use christinacdl/BERT_Offensive_English_Twitter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use christinacdl/BERT_Offensive_English_Twitter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="christinacdl/BERT_Offensive_English_Twitter")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("christinacdl/BERT_Offensive_English_Twitter") model = AutoModelForSequenceClassification.from_pretrained("christinacdl/BERT_Offensive_English_Twitter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6eeaccceebe3478925909d68807aeb640b551dc8a161927c8b93b53b6219683b
- Size of remote file:
- 3.64 kB
- SHA256:
- 7672c1e1eb30db0a877a333b5e3a1bae243a476f8e1b3c1e8bd267a2e81dd5b3
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