Instructions to use badrabbitt/bert_text_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use badrabbitt/bert_text_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="badrabbitt/bert_text_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("badrabbitt/bert_text_classification") model = AutoModelForSequenceClassification.from_pretrained("badrabbitt/bert_text_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c920ba42dfe315e33c72a926857c5b057de376c51cd8f088a04ce3adf7aab097
- Size of remote file:
- 4.98 kB
- SHA256:
- e1e848e284cc35456de1a5a4535cd0e2f91df1a9d0c34b340393ffc1ba400e4a
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