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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c86e0666e9a5d8808c6e5e13295febf6a252738e93eca67c7c8e12fbd0620541
- Size of remote file:
- 536 MB
- SHA256:
- 675207e42cb9771234a18cd05e4157e1010d362a8c9da9b6abb3d19bb9a54f8e
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