Instructions to use DanielSc4/mBERT-formal-informal-EN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DanielSc4/mBERT-formal-informal-EN with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DanielSc4/mBERT-formal-informal-EN")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DanielSc4/mBERT-formal-informal-EN") model = AutoModelForSequenceClassification.from_pretrained("DanielSc4/mBERT-formal-informal-EN") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f820da39225eed084e99bee813a6f6624bd6324054cfa17f3beb3ac7ed5e63dc
- Size of remote file:
- 4.98 kB
- SHA256:
- 09c05dc34d2cada0e4832ff3cd402142dfda652aae4776b29171cc3dfd17e792
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