Instructions to use dthang16/bert_for_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dthang16/bert_for_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dthang16/bert_for_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dthang16/bert_for_classification") model = AutoModelForSequenceClassification.from_pretrained("dthang16/bert_for_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9aaee8767bab0149b55cd874eb5e1e3840e8460d6cdfa3a076eb2f3d9a12090a
- Size of remote file:
- 433 MB
- SHA256:
- 467f0ae1ce135ddb6386bda601e9d4f6afb8f77b36a0db425c335b839c99f135
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