Instructions to use mcanoglu/bigcode-starcoderbase-1b-finetuned-defect-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mcanoglu/bigcode-starcoderbase-1b-finetuned-defect-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mcanoglu/bigcode-starcoderbase-1b-finetuned-defect-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mcanoglu/bigcode-starcoderbase-1b-finetuned-defect-detection") model = AutoModelForSequenceClassification.from_pretrained("mcanoglu/bigcode-starcoderbase-1b-finetuned-defect-detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39838fd9d3112746577241c6d5504b9af17be10ca834087ddd944b6903df7e88
- Size of remote file:
- 4.79 kB
- SHA256:
- d6968a1269359f573f4904b02444182128f06bf7239b66fcbc2621eedc20d105
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