Instructions to use krotima1/AlignScoreCS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use krotima1/AlignScoreCS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="krotima1/AlignScoreCS")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("krotima1/AlignScoreCS") model = AutoModelForSequenceClassification.from_pretrained("krotima1/AlignScoreCS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6dd830c1aaa88daf3612bea4c48280a395d9fd7a4605c83ede19581d55d8692c
- Size of remote file:
- 2.24 GB
- SHA256:
- 8fcb35efab789274b0510a7044c4c987d9058c157311ead3f3f3e4a09908b0f1
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