Instructions to use ShihTing/KaggleAI4Code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ShihTing/KaggleAI4Code with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ShihTing/KaggleAI4Code")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ShihTing/KaggleAI4Code") model = AutoModelForSequenceClassification.from_pretrained("ShihTing/KaggleAI4Code") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed5fa285db436a14e88ac73d220eafdd68ab34f52433250dcc6f9cf3640736bc
- Size of remote file:
- 438 MB
- SHA256:
- 1e0aa8cb667ba5554bfda7350fd39aa33bf33212eac4b571358e4450bf0558e1
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