Instructions to use TehranNLP-org/bert-base-uncased-cls-hatexplain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TehranNLP-org/bert-base-uncased-cls-hatexplain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TehranNLP-org/bert-base-uncased-cls-hatexplain")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TehranNLP-org/bert-base-uncased-cls-hatexplain") model = AutoModelForSequenceClassification.from_pretrained("TehranNLP-org/bert-base-uncased-cls-hatexplain") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7efd0a410c73f615c5da87044244aa7bf4ecab95f442f886c2c01b546d6e3cb9
- Size of remote file:
- 438 MB
- SHA256:
- d93db56f43629245bc0a1f514cba3dd099d0f0c3e55e6204c23d9927a72e9ad0
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