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:
- a9dd676ce0b54d400f645391b74cbbc2c1860703653a858c876cd85de76f7713
- Size of remote file:
- 14.2 kB
- SHA256:
- 76d2b21de1f75cf4cfeaae79e1d9149037272d522e6a1fd7c551b4028a9f7e25
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