Token Classification
Transformers
PyTorch
English
bert
bias-detection
social-bias
gus-net
fairness
interpretability
Instructions to use pinthoz/gus-net-bert-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pinthoz/gus-net-bert-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pinthoz/gus-net-bert-large")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("pinthoz/gus-net-bert-large") model = AutoModelForTokenClassification.from_pretrained("pinthoz/gus-net-bert-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 323a79719935c0d787f8139c169d0b842859ca276a5201ae95ead7ede0b27ae4
- Size of remote file:
- 156 Bytes
- SHA256:
- f6ed2d297b7babd1b7d6147da2983b1f903d95248193c4df00a6f13018e0b222
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