Instructions to use afkpk/bert-1-emergency-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use afkpk/bert-1-emergency-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="afkpk/bert-1-emergency-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("afkpk/bert-1-emergency-classifier") model = AutoModelForSequenceClassification.from_pretrained("afkpk/bert-1-emergency-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e9ee142136345e6ac99503553237055bfe128825b45891491f94f3dbe2d4aaf
- Size of remote file:
- 438 MB
- SHA256:
- a5f896228077b2c487f232d05e1cd765effc7d76eaa3c3b86f42f2832a08d406
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