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:
- 6d9d2e163f3ca77cec84976a2bec3686b98c13847233f0bd89f146027d2b008a
- Size of remote file:
- 1.34 GB
- SHA256:
- 3228cba26e189e6a9e33ce0872b2fd3663b72029865956f4f53320203591dfb3
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