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:
- cea00617584424d22d7888b2a64b323119ee7e004d830ed7a1929eb2daa6150a
- Size of remote file:
- 1.44 GB
- SHA256:
- 6142802eb5b400eddaf019115e682b5b4a80b4f3a244c20519c7753b0cbcd291
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