Instructions to use anyu205/codebert-code-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anyu205/codebert-code-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anyu205/codebert-code-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anyu205/codebert-code-detection") model = AutoModelForSequenceClassification.from_pretrained("anyu205/codebert-code-detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9200cf522e64a03a8599282e966e0e23a9f158e4a5cebaea645e38b9380a068c
- Size of remote file:
- 499 MB
- SHA256:
- b9da453f1e00180dd269625ca9f9738ba148a34b925a46dc08999d25c562d312
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