Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
bert
fill-mask
Generated from Trainer
Instructions to use maximuspowers/bert-philosophy-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maximuspowers/bert-philosophy-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="maximuspowers/bert-philosophy-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("maximuspowers/bert-philosophy-classifier") model = AutoModelForMaskedLM.from_pretrained("maximuspowers/bert-philosophy-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3831855c8279d1acd570bd377a05092bc1f4ff02920ccafb68cc25eae163e80
- Size of remote file:
- 441 MB
- SHA256:
- 1207fa3962d04f8e57c1fdaeed866e81adabce8138756fe502348b0182ec17fa
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