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:
- 3f3a5aec68e078837fafe5ffae62af5490ebf042044225a0f51cdbcb139350c7
- Size of remote file:
- 4.55 GB
- SHA256:
- 2127f62c21723d8676fa2b820ff6f99a031af22d0564351b7e6ac1b760951084
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