Instructions to use ThuyNT03/CS431_Vi-COQE_CSI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThuyNT03/CS431_Vi-COQE_CSI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ThuyNT03/CS431_Vi-COQE_CSI")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ThuyNT03/CS431_Vi-COQE_CSI") model = AutoModelForSequenceClassification.from_pretrained("ThuyNT03/CS431_Vi-COQE_CSI") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e6dc1de7cfffb18697f5c915ff5a803ef4a899bc5402a5d7717c0b30f34c2776
- Size of remote file:
- 4.16 kB
- SHA256:
- cabbfdd894b4199b89ffe217f5f8c7a50dd994451d2786b91a7b2fb29859cdf8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.