Token Classification
Transformers
PyTorch
English
gpt2
bias-detection
social-bias
gus-net
fairness
interpretability
text-generation-inference
Instructions to use pinthoz/gus-net-gpt2-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pinthoz/gus-net-gpt2-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pinthoz/gus-net-gpt2-medium")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("pinthoz/gus-net-gpt2-medium") model = AutoModelForTokenClassification.from_pretrained("pinthoz/gus-net-gpt2-medium", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 119a67644d33e9c05e4c30cc1898067fcef039fe09246b29a0296fc2849afda9
- Size of remote file:
- 4.63 kB
- SHA256:
- b01941a53cafd85a99c9bff0cc2f1402294ab1bb901a19add338b3519c2a547f
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