Instructions to use JoshuaAAX/bert-base-uncased-binary-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JoshuaAAX/bert-base-uncased-binary-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JoshuaAAX/bert-base-uncased-binary-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JoshuaAAX/bert-base-uncased-binary-classification") model = AutoModelForSequenceClassification.from_pretrained("JoshuaAAX/bert-base-uncased-binary-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a72fc629cd8c2aa3596afddbb101d304bb40d680e08a57a71cde380e407b9d42
- Size of remote file:
- 5.78 kB
- SHA256:
- 2ce5672c257905bac6cb80cce8de9aabe68157ca4ce28aa4f8d27edd8dba357d
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