Text Classification
Transformers
PyTorch
Hebrew
bert
feature-extraction
code
text-embeddings-inference
Instructions to use SinaLab/Offensive-Hebrew with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SinaLab/Offensive-Hebrew with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SinaLab/Offensive-Hebrew")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SinaLab/Offensive-Hebrew") model = AutoModel.from_pretrained("SinaLab/Offensive-Hebrew") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4be6e71f181a4f9444e9985bc4ef6798818d41e66bec6e1c18778954fff491e1
- Size of remote file:
- 1.51 GB
- SHA256:
- c9bf56387f858a0d2bf1e956ae47182345e22356f78df076eb227815204fe8b4
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