Instructions to use liamliang/demographics_race with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use liamliang/demographics_race with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="liamliang/demographics_race")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("liamliang/demographics_race") model = AutoModelForSequenceClassification.from_pretrained("liamliang/demographics_race") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c34877fa0e7a65e6556b2ca67ead473d910daf3f70666f01f6547317e0927c8
- Size of remote file:
- 438 MB
- SHA256:
- c4ddb15422d6484b2269c07ee20b460288bbf70fafd9221db43d40922567f7d0
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