Instructions to use edwindn/bert_rag_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edwindn/bert_rag_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="edwindn/bert_rag_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("edwindn/bert_rag_classifier") model = AutoModelForSequenceClassification.from_pretrained("edwindn/bert_rag_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0f5c13d3934a50f409dab1d5bbc456709c6a2d6c0cdf9d1f5ee10f693f14cb57
- Size of remote file:
- 438 MB
- SHA256:
- 8adfa8ad3815f301f656133c85ac1ca83e9a2611b27c611e30ea3088e094a5f2
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