Instructions to use SLKpnu/text_clf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SLKpnu/text_clf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SLKpnu/text_clf")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SLKpnu/text_clf") model = AutoModelForSequenceClassification.from_pretrained("SLKpnu/text_clf") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- edff6fdfcc2cdf780e7cd0b469b756acbccbf3219228afe0e47d32dfa0f59da4
- Size of remote file:
- 1.06 kB
- SHA256:
- 7af99a8771cbf6f19faee7183ef06b0cb12033a679e66ad2f10dc3b2030aef2d
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