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")# pip install -U transformers accelerate # 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
Download tokenizer.json from pinthoz/gus-net-bert-large: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/pinthoz/gus-net-bert-large/resolve/main/tokenizer.json
- Command line
-
hf download hf://pinthoz/gus-net-bert-large/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/pinthoz/gus-net-bert-large/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.