Instructions to use samim2024/bert-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use samim2024/bert-text-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="samim2024/bert-text-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("samim2024/bert-text-classification") model = AutoModelForSequenceClassification.from_pretrained("samim2024/bert-text-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fccb96d779e5a5fdefe09d9e93d7ff0ac1f2ac594d87bd1b8a1037d89b789460
- Size of remote file:
- 5.37 kB
- SHA256:
- b63c47c7f9208f6c2d2b334acc7f83b3b5cfed409fd3dab074fb320aaf9b3831
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