Instructions to use Cameron/BERT-Jigsaw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cameron/BERT-Jigsaw with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cameron/BERT-Jigsaw")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cameron/BERT-Jigsaw") model = AutoModelForSequenceClassification.from_pretrained("Cameron/BERT-Jigsaw") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b4f7ceeeea69302bdff6f245be2282513b6f8e35153641e73cfa7d8ec2f46ad
- Size of remote file:
- 433 MB
- SHA256:
- d2f7d0e4c20100e9ff6bd483f1b42b50957b2d675016bf6f0bf8b3180f0f4b99
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