Instructions to use yevhenkost/classifier__generated_data_only__potencialsdetection_albert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yevhenkost/classifier__generated_data_only__potencialsdetection_albert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yevhenkost/classifier__generated_data_only__potencialsdetection_albert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yevhenkost/classifier__generated_data_only__potencialsdetection_albert") model = AutoModelForSequenceClassification.from_pretrained("yevhenkost/classifier__generated_data_only__potencialsdetection_albert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 77a0e73c7fa145bc7c7c9816d230b882c502d41c85d7bf764a770ca9614ba403
- Size of remote file:
- 46.8 MB
- SHA256:
- 8bd5c7af26b3e6bd8019196c4cd16230711bca0314c9c86b78f3e9d9d911fef4
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