Instructions to use procit007/Classification_Model_june25_resampling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use procit007/Classification_Model_june25_resampling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="procit007/Classification_Model_june25_resampling")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("procit007/Classification_Model_june25_resampling") model = AutoModelForSequenceClassification.from_pretrained("procit007/Classification_Model_june25_resampling") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d13ae7e20c8f4f438663e83818f3dcf66c68074d801970e118475579a80596ac
- Size of remote file:
- 439 MB
- SHA256:
- c9efdb0f742041fe008b5f05180e4b5c6359a74ae8b37125892d98b048ef7f9a
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