Instructions to use iolimat482/common-core-bert-hierarchical-classification_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iolimat482/common-core-bert-hierarchical-classification_v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="iolimat482/common-core-bert-hierarchical-classification_v3")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("iolimat482/common-core-bert-hierarchical-classification_v3", dtype="auto") - Notebooks
- Google Colab
- Kaggle
BERT Hierarchical Classification Model
This model is a fine-tuned BERT-based model for hierarchical classification of Common Core Standard questions.
Model Description
The model classifies input texts into the following hierarchical levels:
- Grade
- Domain
- Cluster
- Standard
Files
config.json: Model configuration.pytorch_model.bin: Model weights.modeling.py: Model class definition.tokenizer/: Tokenizer files.label_encoders.joblib: Label encoders for mapping predictions back to labels.
Usage
See instructions below on how to load and use the model.
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Model tree for iolimat482/common-core-bert-hierarchical-classification_v3
Base model
google-bert/bert-base-uncased