Token Classification
Transformers
PyTorch
Safetensors
English
bert
bias-detection
social-bias
gus-net
fairness
interpretability
Instructions to use pinthoz/gus-net-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pinthoz/gus-net-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pinthoz/gus-net-bert", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("pinthoz/gus-net-bert") model = AutoModelForTokenClassification.from_pretrained("pinthoz/gus-net-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Replace with paper-clean model (punct-fixed dataset, focal loss)
Browse files- optimized_thresholds.npy +1 -1
- pytorch_model.bin +1 -1
optimized_thresholds.npy
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