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:
- dc5342ffb96d234bf7e3d4601f09e90a1cea12892b7e479d383e3b23c28356bf
- Size of remote file:
- 5.37 kB
- SHA256:
- cf6748b3526bd2bb2cfd14cd9a332c16df6f583a7a6a8dcbf0d79f3da2ede92f
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