Instructions to use Santarabantoosoo/path_bert_undersampling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Santarabantoosoo/path_bert_undersampling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Santarabantoosoo/path_bert_undersampling")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Santarabantoosoo/path_bert_undersampling") model = AutoModelForSequenceClassification.from_pretrained("Santarabantoosoo/path_bert_undersampling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8af44e609813ef7af7c6527276b2b91b60656df90b4426bb3fa768400dcad780
- Size of remote file:
- 384 MB
- SHA256:
- d1c223265409d7901101888356bd8f8b14a8840a01c9b6aa2751f1649810d42a
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