Instructions to use Cameron/BERT-rtgender-opgender-annotations with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cameron/BERT-rtgender-opgender-annotations with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cameron/BERT-rtgender-opgender-annotations")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cameron/BERT-rtgender-opgender-annotations") model = AutoModelForSequenceClassification.from_pretrained("Cameron/BERT-rtgender-opgender-annotations") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d253bb6d3b8f4804b7bfc7066bfd928a3d35f3fdb39c19c8d92524d6bd9fe7a
- Size of remote file:
- 433 MB
- SHA256:
- 2bf8e128d667b81621016608aa9916dbde10b181da7c907b500c436cc0122cb5
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